Overview

Dataset statistics

Number of variables373
Number of observations107
Missing cells1480
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory311.9 KiB
Average record size in memory2.9 KiB

Variable types

Numeric371
Categorical2

Warnings

Libellé index \ CGD has a high cardinality: 104 distinct values High cardinality
CGD BELLEY has 4 (3.7%) missing values Missing
CGD BOURG EN BRESSE has 4 (3.7%) missing values Missing
CGD GEX has 4 (3.7%) missing values Missing
CGD TREVOUX has 4 (3.7%) missing values Missing
CGD CHATEAU THIERRY NOGENTEL has 4 (3.7%) missing values Missing
CGD LAON has 4 (3.7%) missing values Missing
CGD SOISSONS has 4 (3.7%) missing values Missing
CGD ST QUENTIN has 4 (3.7%) missing values Missing
CGD VERVINS has 4 (3.7%) missing values Missing
CGD MONTLUCON has 4 (3.7%) missing values Missing
CGD MOULINS has 4 (3.7%) missing values Missing
CGD VICHY has 4 (3.7%) missing values Missing
CGD BARCELONNETTE has 4 (3.7%) missing values Missing
CGD CASTELLANE has 4 (3.7%) missing values Missing
CGD DIGNE LES BAINS has 4 (3.7%) missing values Missing
CGD FORCALQUIER has 4 (3.7%) missing values Missing
CGD BRIANCON has 4 (3.7%) missing values Missing
CGD GAP has 4 (3.7%) missing values Missing
CGD CANNES has 4 (3.7%) missing values Missing
CGD GRASSE has 4 (3.7%) missing values Missing
CGD MENTON has 4 (3.7%) missing values Missing
CGD NICE has 4 (3.7%) missing values Missing
CGD PUGET THENIERS has 4 (3.7%) missing values Missing
CGD LARGENTIERE has 4 (3.7%) missing values Missing
CGD LE TEIL has 4 (3.7%) missing values Missing
CGD TOURNON SUR RHONE has 4 (3.7%) missing values Missing
CGD RETHEL has 4 (3.7%) missing values Missing
CGD REVIN has 4 (3.7%) missing values Missing
CGD SEDAN has 4 (3.7%) missing values Missing
CGD VOUZIERS has 4 (3.7%) missing values Missing
CGD FOIX has 4 (3.7%) missing values Missing
CGD PAMIERS has 4 (3.7%) missing values Missing
CGD ST GIRONS has 4 (3.7%) missing values Missing
CGD BAR SUR AUBE has 4 (3.7%) missing values Missing
CGD NOGENT SUR SEINE has 4 (3.7%) missing values Missing
CGD ROSIERES PRES TROYES has 4 (3.7%) missing values Missing
CGD CARCASSONNE has 4 (3.7%) missing values Missing
CGD LIMOUX has 4 (3.7%) missing values Missing
CGD NARBONNE has 4 (3.7%) missing values Missing
CGD MILLAU has 4 (3.7%) missing values Missing
CGD RODEZ has 4 (3.7%) missing values Missing
CGD VILLEFRANCHE DE ROUERGUE has 4 (3.7%) missing values Missing
CGD AIX EN PROVENCE has 4 (3.7%) missing values Missing
CGD ARLES has 4 (3.7%) missing values Missing
CGD AUBAGNE has 4 (3.7%) missing values Missing
CGD ISTRES has 4 (3.7%) missing values Missing
CGD SALON DE PROVENCE has 4 (3.7%) missing values Missing
CGD BAYEUX has 4 (3.7%) missing values Missing
CGD CAEN has 4 (3.7%) missing values Missing
CGD DEAUVILLE has 4 (3.7%) missing values Missing
CGD FALAISE has 4 (3.7%) missing values Missing
CGD LISIEUX has 4 (3.7%) missing values Missing
CGD VIRE NORMANDIE has 4 (3.7%) missing values Missing
CGD AURILLAC has 4 (3.7%) missing values Missing
CGD MAURIAC has 4 (3.7%) missing values Missing
CGD ST FLOUR has 4 (3.7%) missing values Missing
CGD ANGOULEME has 4 (3.7%) missing values Missing
CGD COGNAC has 4 (3.7%) missing values Missing
CGD CONFOLENS has 4 (3.7%) missing values Missing
CGD JONZAC has 4 (3.7%) missing values Missing
CGD LA ROCHELLE has 4 (3.7%) missing values Missing
CGD ROCHEFORT has 4 (3.7%) missing values Missing
CGD SAINTES has 4 (3.7%) missing values Missing
CGD ST JEAN D ANGELY has 4 (3.7%) missing values Missing
CGD BOURGES has 4 (3.7%) missing values Missing
CGD ST AMAND MONTROND has 4 (3.7%) missing values Missing
CGD VIERZON has 4 (3.7%) missing values Missing
CGD BRIVE LA GAILLARDE has 4 (3.7%) missing values Missing
CGD USSEL has 4 (3.7%) missing values Missing
CGD BEAUNE has 4 (3.7%) missing values Missing
CGD DIJON has 4 (3.7%) missing values Missing
CGD IS SUR TILLE has 4 (3.7%) missing values Missing
CGD MONTBARD has 4 (3.7%) missing values Missing
CGD DINAN has 4 (3.7%) missing values Missing
CGD GUINGAMP has 4 (3.7%) missing values Missing
CGD LANNION has 4 (3.7%) missing values Missing
CGD ST BRIEUC has 4 (3.7%) missing values Missing
CGD AUBUSSON has 4 (3.7%) missing values Missing
CGD GUERET has 4 (3.7%) missing values Missing
CGD BERGERAC has 4 (3.7%) missing values Missing
CGD NONTRON has 4 (3.7%) missing values Missing
CGD PERIGUEUX has 4 (3.7%) missing values Missing
CGD SARLAT LA CANEDA has 4 (3.7%) missing values Missing
CGD BESANCON has 4 (3.7%) missing values Missing
CGD MONTBELIARD has 4 (3.7%) missing values Missing
CGD PONTARLIER has 4 (3.7%) missing values Missing
CGD CREST has 4 (3.7%) missing values Missing
CGD NYONS has 4 (3.7%) missing values Missing
CGD PIERRELATTE has 4 (3.7%) missing values Missing
CGD ROMANS SUR ISERE has 4 (3.7%) missing values Missing
CGD BERNAY has 4 (3.7%) missing values Missing
CGD EVREUX has 4 (3.7%) missing values Missing
CGD LES ANDELYS has 4 (3.7%) missing values Missing
CGD LOUVIERS has 4 (3.7%) missing values Missing
CGD PONT AUDEMER has 4 (3.7%) missing values Missing
CGD CHATEAUDUN has 4 (3.7%) missing values Missing
CGD DREUX has 4 (3.7%) missing values Missing
CGD LUCE has 4 (3.7%) missing values Missing
CGD NOGENT LE ROTROU has 4 (3.7%) missing values Missing
CGD BREST has 4 (3.7%) missing values Missing
CGD CHATEAULIN has 4 (3.7%) missing values Missing
CGD LANDERNEAU has 4 (3.7%) missing values Missing
CGD PLOURIN LES MORLAIX has 4 (3.7%) missing values Missing
CGD QUIMPER has 4 (3.7%) missing values Missing
CGD QUIMPERLE has 4 (3.7%) missing values Missing
CGD AJACCIO has 4 (3.7%) missing values Missing
CGD PORTO VECCHIO has 4 (3.7%) missing values Missing
CGD SARTENE has 4 (3.7%) missing values Missing
CGD BASTIA has 4 (3.7%) missing values Missing
CGD CALVI has 4 (3.7%) missing values Missing
CGD CORTE has 4 (3.7%) missing values Missing
CGD GHISONACCIA has 4 (3.7%) missing values Missing
CGD ALES has 4 (3.7%) missing values Missing
CGD BAGNOLS SUR CEZE has 4 (3.7%) missing values Missing
CGD LE VIGAN has 4 (3.7%) missing values Missing
CGD NIMES has 4 (3.7%) missing values Missing
CGD VAUVERT has 4 (3.7%) missing values Missing
CGD MURET has 4 (3.7%) missing values Missing
CGD ST GAUDENS has 4 (3.7%) missing values Missing
CGD TOULOUSE MIRAIL has 4 (3.7%) missing values Missing
CGD TOULOUSE ST MICHEL has 4 (3.7%) missing values Missing
CGD VILLEFRANCHE DE LAURAGAIS has 4 (3.7%) missing values Missing
CGD AUCH has 4 (3.7%) missing values Missing
CGD CONDOM has 4 (3.7%) missing values Missing
CGD ARCACHON has 4 (3.7%) missing values Missing
CGD BLAYE has 4 (3.7%) missing values Missing
CGD BOULIAC has 4 (3.7%) missing values Missing
CGD LANGON TOULENNE has 4 (3.7%) missing values Missing
CGD LESPARRE MEDOC has 4 (3.7%) missing values Missing
CGD LIBOURNE has 4 (3.7%) missing values Missing
CGD MERIGNAC has 4 (3.7%) missing values Missing
CGD BEZIERS has 4 (3.7%) missing values Missing
CGD CASTELNAU LE LEZ has 4 (3.7%) missing values Missing
CGD LODEVE has 4 (3.7%) missing values Missing
CGD LUNEL has 4 (3.7%) missing values Missing
CGD PEZENAS has 4 (3.7%) missing values Missing
CGD MONTFORT SUR MEU has 4 (3.7%) missing values Missing
CGD REDON has 4 (3.7%) missing values Missing
CGD RENNES has 4 (3.7%) missing values Missing
CGD ST MALO has 4 (3.7%) missing values Missing
CGD VITRE has 4 (3.7%) missing values Missing
CGD ISSOUDUN has 4 (3.7%) missing values Missing
CGD LA CHATRE has 4 (3.7%) missing values Missing
CGD LE BLANC has 4 (3.7%) missing values Missing
CGD AMBOISE has 4 (3.7%) missing values Missing
CGD CHINON has 4 (3.7%) missing values Missing
CGD LOCHES has 4 (3.7%) missing values Missing
CGD TOURS has 4 (3.7%) missing values Missing
CGD BOURGOIN JALLIEU has 4 (3.7%) missing values Missing
CGD GRENOBLE has 4 (3.7%) missing values Missing
CGD LA MURE has 4 (3.7%) missing values Missing
CGD LA TOUR DU PIN has 4 (3.7%) missing values Missing
CGD MEYLAN has 4 (3.7%) missing values Missing
CGD ST MARCELLIN has 4 (3.7%) missing values Missing
CGD VIENNE has 4 (3.7%) missing values Missing
CGD DOLE has 4 (3.7%) missing values Missing
CGD LONS LE SAUNIER has 4 (3.7%) missing values Missing
CGD ST CLAUDE has 4 (3.7%) missing values Missing
CGD DAX has 4 (3.7%) missing values Missing
CGD MONT DE MARSAN has 4 (3.7%) missing values Missing
CGD PARENTIS EN BORN has 4 (3.7%) missing values Missing
CGD BLOIS has 4 (3.7%) missing values Missing
CGD ROMORANTIN LANTHENAY has 4 (3.7%) missing values Missing
CGD VENDOME has 4 (3.7%) missing values Missing
CGD MONTBRISON has 4 (3.7%) missing values Missing
CGD ROANNE has 4 (3.7%) missing values Missing
CGD ST ETIENNE has 4 (3.7%) missing values Missing
CGD BRIOUDE has 4 (3.7%) missing values Missing
CGD LE PUY EN VELAY has 4 (3.7%) missing values Missing
CGD YSSINGEAUX has 4 (3.7%) missing values Missing
CGD ANCENIS ST GEREON has 4 (3.7%) missing values Missing
CGD CHATEAUBRIANT has 4 (3.7%) missing values Missing
CGD NANTES has 4 (3.7%) missing values Missing
CGD PORNIC has 4 (3.7%) missing values Missing
CGD REZE has 4 (3.7%) missing values Missing
CGD ST NAZAIRE has 4 (3.7%) missing values Missing
CGD GIEN has 4 (3.7%) missing values Missing
CGD MONTARGIS has 4 (3.7%) missing values Missing
CGD ORLEANS has 4 (3.7%) missing values Missing
CGD PITHIVIERS has 4 (3.7%) missing values Missing
CGD CAHORS has 4 (3.7%) missing values Missing
CGD FIGEAC has 4 (3.7%) missing values Missing
CGD GOURDON has 4 (3.7%) missing values Missing
CGD AGEN has 4 (3.7%) missing values Missing
CGD MARMANDE has 4 (3.7%) missing values Missing
CGD VILLENEUVE SUR LOT has 4 (3.7%) missing values Missing
CGD FLORAC TROIS RIVIERES has 4 (3.7%) missing values Missing
CGD MENDE has 4 (3.7%) missing values Missing
CGD ANGERS has 4 (3.7%) missing values Missing
CGD CHOLET has 4 (3.7%) missing values Missing
CGD SAUMUR has 4 (3.7%) missing values Missing
CGD SEGRE EN ANJOU BLEU has 4 (3.7%) missing values Missing
CGD AVRANCHES has 4 (3.7%) missing values Missing
CGD CHERBOURG EN COTENTIN has 4 (3.7%) missing values Missing
CGD COUTANCES has 4 (3.7%) missing values Missing
CGD ST LO has 4 (3.7%) missing values Missing
CGD CHALONS EN CHAMPAGNE has 4 (3.7%) missing values Missing
CGD EPERNAY has 4 (3.7%) missing values Missing
CGD REIMS has 4 (3.7%) missing values Missing
CGD VITRY LE FRANCOIS has 4 (3.7%) missing values Missing
CGD CHAUMONT has 4 (3.7%) missing values Missing
CGD LANGRES has 4 (3.7%) missing values Missing
CGD ST DIZIER has 4 (3.7%) missing values Missing
CGD CHATEAU GONTIER SUR MAYENNE has 4 (3.7%) missing values Missing
CGD MAYENNE has 4 (3.7%) missing values Missing
CGD LUNEVILLE has 4 (3.7%) missing values Missing
CGD NANCY has 4 (3.7%) missing values Missing
CGD TOUL has 4 (3.7%) missing values Missing
CGD VAL DE BRIEY has 4 (3.7%) missing values Missing
CGD COMMERCY has 4 (3.7%) missing values Missing
CGD VERDUN has 4 (3.7%) missing values Missing
CGD LORIENT has 4 (3.7%) missing values Missing
CGD PLOERMEL has 4 (3.7%) missing values Missing
CGD PONTIVY has 4 (3.7%) missing values Missing
CGD VANNES has 4 (3.7%) missing values Missing
CGD BOULAY MOSELLE has 4 (3.7%) missing values Missing
CGD FORBACH has 4 (3.7%) missing values Missing
CGD METZ has 4 (3.7%) missing values Missing
CGD SARREBOURG has 4 (3.7%) missing values Missing
CGD SARREGUEMINES has 4 (3.7%) missing values Missing
CGD THIONVILLE has 4 (3.7%) missing values Missing
CGD CHATEAU CHINON VILLE has 4 (3.7%) missing values Missing
CGD COSNE COURS SUR LOIRE has 4 (3.7%) missing values Missing
CGD NEVERS has 4 (3.7%) missing values Missing
CGD AVESNES SUR HELPE has 4 (3.7%) missing values Missing
CGD CAMBRAI has 4 (3.7%) missing values Missing
CGD DOUAI has 4 (3.7%) missing values Missing
CGD DUNKERQUE HOYMILLE has 4 (3.7%) missing values Missing
CGD HAZEBROUCK has 4 (3.7%) missing values Missing
CGD LILLE has 4 (3.7%) missing values Missing
CGD VALENCIENNES has 4 (3.7%) missing values Missing
CGD BEAUVAIS has 4 (3.7%) missing values Missing
CGD CHANTILLY has 4 (3.7%) missing values Missing
CGD CLERMONT has 4 (3.7%) missing values Missing
CGD COMPIEGNE has 4 (3.7%) missing values Missing
CGD MERU has 4 (3.7%) missing values Missing
CGD SENLIS has 4 (3.7%) missing values Missing
CGD ALENCON ARGENTAN has 4 (3.7%) missing values Missing
CGD DOMFRONT EN POIRAIE has 4 (3.7%) missing values Missing
CGD MORTAGNE AU PERCHE has 4 (3.7%) missing values Missing
CGD ARRAS has 4 (3.7%) missing values Missing
CGD BETHUNE has 4 (3.7%) missing values Missing
CGD CALAIS has 4 (3.7%) missing values Missing
CGD ECUIRES has 4 (3.7%) missing values Missing
CGD ST OMER has 4 (3.7%) missing values Missing
CGD ST POL SUR TERNOISE has 4 (3.7%) missing values Missing
CGD AMBERT has 4 (3.7%) missing values Missing
CGD CLERMONT FERRAND has 4 (3.7%) missing values Missing
CGD ISSOIRE has 4 (3.7%) missing values Missing
CGD RIOM has 4 (3.7%) missing values Missing
CGD THIERS has 4 (3.7%) missing values Missing
CGD BAYONNE has 4 (3.7%) missing values Missing
CGD OLORON STE MARIE has 4 (3.7%) missing values Missing
CGD ORTHEZ has 4 (3.7%) missing values Missing
CGD PAU has 4 (3.7%) missing values Missing
CGD ARGELES GAZOST has 4 (3.7%) missing values Missing
CGD BAGNERES DE BIGORRE has 4 (3.7%) missing values Missing
CGD TARBES has 4 (3.7%) missing values Missing
CGD CERET has 4 (3.7%) missing values Missing
CGD PERPIGNAN has 4 (3.7%) missing values Missing
CGD PRADES has 4 (3.7%) missing values Missing
CGD RIVESALTES has 4 (3.7%) missing values Missing
CGD HAGUENAU has 4 (3.7%) missing values Missing
CGD MOLSHEIM has 4 (3.7%) missing values Missing
CGD SAVERNE has 4 (3.7%) missing values Missing
CGD SELESTAT has 4 (3.7%) missing values Missing
CGD STRASBOURG has 4 (3.7%) missing values Missing
CGD WISSEMBOURG has 4 (3.7%) missing values Missing
CGD ALTKIRCH has 4 (3.7%) missing values Missing
CGD COLMAR has 4 (3.7%) missing values Missing
CGD MULHOUSE has 4 (3.7%) missing values Missing
CGD SOULTZ GUEBWILLER has 4 (3.7%) missing values Missing
CGD BRON has 4 (3.7%) missing values Missing
CGD GIVORS has 4 (3.7%) missing values Missing
CGD L ARBRESLE has 4 (3.7%) missing values Missing
CGD LYON has 4 (3.7%) missing values Missing
CGD VILLEFRANCHE SUR SAONE has 4 (3.7%) missing values Missing
CGD LURE has 4 (3.7%) missing values Missing
CGD VESOUL has 4 (3.7%) missing values Missing
CGD AUTUN has 4 (3.7%) missing values Missing
CGD CHALON SUR SAONE has 4 (3.7%) missing values Missing
CGD CHAROLLES has 4 (3.7%) missing values Missing
CGD LOUHANS has 4 (3.7%) missing values Missing
CGD MACON has 4 (3.7%) missing values Missing
CGD LA FLECHE has 4 (3.7%) missing values Missing
CGD LE MANS has 4 (3.7%) missing values Missing
CGD MAMERS has 4 (3.7%) missing values Missing
CGD ALBERTVILLE has 4 (3.7%) missing values Missing
CGD CHAMBERY has 4 (3.7%) missing values Missing
CGD ST JEAN DE MAURIENNE has 4 (3.7%) missing values Missing
CGD ANNECY has 4 (3.7%) missing values Missing
CGD BONNEVILLE has 4 (3.7%) missing values Missing
CGD CHAMONIX MONT BLANC has 4 (3.7%) missing values Missing
CGD ST JULIEN EN GENEVOIS has 4 (3.7%) missing values Missing
CGD THONON LES BAINS has 4 (3.7%) missing values Missing
CGD DIEPPE has 4 (3.7%) missing values Missing
CGD FECAMP has 4 (3.7%) missing values Missing
CGD LE HAVRE has 4 (3.7%) missing values Missing
CGD NEUFCHATEL EN BRAY has 4 (3.7%) missing values Missing
CGD ROUEN has 4 (3.7%) missing values Missing
CGD YVETOT has 4 (3.7%) missing values Missing
CGD COULOMMIERS has 4 (3.7%) missing values Missing
CGD FONTAINEBLEAU has 4 (3.7%) missing values Missing
CGD MEAUX has 4 (3.7%) missing values Missing
CGD MELUN has 4 (3.7%) missing values Missing
CGD PROVINS has 4 (3.7%) missing values Missing
CGD MANTES LA JOLIE has 4 (3.7%) missing values Missing
CGD RAMBOUILLET has 4 (3.7%) missing values Missing
CGD ST GERMAIN EN LAYE has 4 (3.7%) missing values Missing
CGD BRESSUIRE has 4 (3.7%) missing values Missing
CGD NIORT has 4 (3.7%) missing values Missing
CGD PARTHENAY has 4 (3.7%) missing values Missing
CGD ABBEVILLE has 4 (3.7%) missing values Missing
CGD AMIENS has 4 (3.7%) missing values Missing
CGD MONTDIDIER has 4 (3.7%) missing values Missing
CGD PERONNE has 4 (3.7%) missing values Missing
CGD ALBI has 4 (3.7%) missing values Missing
CGD CASTRES has 4 (3.7%) missing values Missing
CGD GAILLAC has 4 (3.7%) missing values Missing
CGD CASTELSARRASIN has 4 (3.7%) missing values Missing
CGD MONTAUBAN has 4 (3.7%) missing values Missing
CGD BRIGNOLES has 4 (3.7%) missing values Missing
CGD DRAGUIGNAN has 4 (3.7%) missing values Missing
CGD GASSIN ST TROPEZ has 4 (3.7%) missing values Missing
CGD HYERES has 4 (3.7%) missing values Missing
CGD LA VALETTE DU VAR has 4 (3.7%) missing values Missing
CGD AVIGNON has 4 (3.7%) missing values Missing
CGD CARPENTRAS has 4 (3.7%) missing values Missing
CGD ORANGE has 4 (3.7%) missing values Missing
CGD PERTUIS has 4 (3.7%) missing values Missing
CGD FONTENAY LE COMTE has 4 (3.7%) missing values Missing
CGD LA ROCHE SUR YON has 4 (3.7%) missing values Missing
CGD LES SABLES D OLONNE has 4 (3.7%) missing values Missing
CGD CHATELLERAULT has 4 (3.7%) missing values Missing
CGD MONTMORILLON has 4 (3.7%) missing values Missing
CGD POITIERS has 4 (3.7%) missing values Missing
CGD BELLAC has 4 (3.7%) missing values Missing
CGD LIMOGES has 4 (3.7%) missing values Missing
CGD ST JUNIEN has 4 (3.7%) missing values Missing
CGD NEUFCHATEAU has 4 (3.7%) missing values Missing
CGD REMIREMONT has 4 (3.7%) missing values Missing
CGD ST DIE DES VOSGES has 4 (3.7%) missing values Missing
CGD AUXERRE has 4 (3.7%) missing values Missing
CGD AVALLON has 4 (3.7%) missing values Missing
CGD SENS has 4 (3.7%) missing values Missing
CGD ETAMPES has 4 (3.7%) missing values Missing
CGD EVRY COURCOURONNES has 4 (3.7%) missing values Missing
CGD PALAISEAU has 4 (3.7%) missing values Missing
CGD L ISLE ADAM has 4 (3.7%) missing values Missing
CGD MONTMORENCY has 4 (3.7%) missing values Missing
CGD PONTOISE has 4 (3.7%) missing values Missing
CGD LE MOULE has 4 (3.7%) missing values Missing
CGD POINTE A PITRE has 4 (3.7%) missing values Missing
CGD ST CLAUDE (971) has 4 (3.7%) missing values Missing
CGD FORT DE FRANCE has 4 (3.7%) missing values Missing
CGD LA TRINITE has 4 (3.7%) missing values Missing
CGD LE MARIN has 4 (3.7%) missing values Missing
CGD KOUROU has 4 (3.7%) missing values Missing
CGD MATOURY has 4 (3.7%) missing values Missing
CGD ST LAURENT DU MARONI has 4 (3.7%) missing values Missing
CGD ST BENOIT has 4 (3.7%) missing values Missing
CGD ST PAUL has 4 (3.7%) missing values Missing
CGD ST PIERRE has 4 (3.7%) missing values Missing
CGD ST MARTIN ST BARTHELEMY has 4 (3.7%) missing values Missing
CGD LES ARCHIPELS PAPEETE has 4 (3.7%) missing values Missing
CGD LES ILES DU VENT FAAA has 4 (3.7%) missing values Missing
CGD KONE has 4 (3.7%) missing values Missing
CGD LA FOA has 4 (3.7%) missing values Missing
CGD NOUMEA has 4 (3.7%) missing values Missing
CGD POINDIMIE has 4 (3.7%) missing values Missing
Code index is uniformly distributed Uniform
Libellé index \ CGD is uniformly distributed Uniform
Code index has unique values Unique
CGD BELLEY has 31 (29.0%) zeros Zeros
CGD BOURG EN BRESSE has 29 (27.1%) zeros Zeros
CGD GEX has 26 (24.3%) zeros Zeros
CGD TREVOUX has 19 (17.8%) zeros Zeros
CGD CHATEAU THIERRY NOGENTEL has 37 (34.6%) zeros Zeros
CGD LAON has 28 (26.2%) zeros Zeros
CGD SOISSONS has 35 (32.7%) zeros Zeros
CGD ST QUENTIN has 39 (36.4%) zeros Zeros
CGD VERVINS has 36 (33.6%) zeros Zeros
CGD MONTLUCON has 37 (34.6%) zeros Zeros
CGD MOULINS has 38 (35.5%) zeros Zeros
CGD VICHY has 35 (32.7%) zeros Zeros
CGD BARCELONNETTE has 52 (48.6%) zeros Zeros
CGD CASTELLANE has 48 (44.9%) zeros Zeros
CGD DIGNE LES BAINS has 34 (31.8%) zeros Zeros
CGD FORCALQUIER has 35 (32.7%) zeros Zeros
CGD BRIANCON has 42 (39.3%) zeros Zeros
CGD GAP has 33 (30.8%) zeros Zeros
CGD CANNES has 20 (18.7%) zeros Zeros
CGD GRASSE has 28 (26.2%) zeros Zeros
CGD MENTON has 31 (29.0%) zeros Zeros
CGD NICE has 28 (26.2%) zeros Zeros
CGD PUGET THENIERS has 37 (34.6%) zeros Zeros
CGD LARGENTIERE has 36 (33.6%) zeros Zeros
CGD LE TEIL has 29 (27.1%) zeros Zeros
CGD TOURNON SUR RHONE has 27 (25.2%) zeros Zeros
CGD RETHEL has 39 (36.4%) zeros Zeros
CGD REVIN has 33 (30.8%) zeros Zeros
CGD SEDAN has 35 (32.7%) zeros Zeros
CGD VOUZIERS has 51 (47.7%) zeros Zeros
CGD FOIX has 36 (33.6%) zeros Zeros
CGD PAMIERS has 33 (30.8%) zeros Zeros
CGD ST GIRONS has 35 (32.7%) zeros Zeros
CGD BAR SUR AUBE has 33 (30.8%) zeros Zeros
CGD NOGENT SUR SEINE has 31 (29.0%) zeros Zeros
CGD ROSIERES PRES TROYES has 28 (26.2%) zeros Zeros
CGD CARCASSONNE has 32 (29.9%) zeros Zeros
CGD LIMOUX has 41 (38.3%) zeros Zeros
CGD NARBONNE has 24 (22.4%) zeros Zeros
CGD MILLAU has 39 (36.4%) zeros Zeros
CGD RODEZ has 35 (32.7%) zeros Zeros
CGD VILLEFRANCHE DE ROUERGUE has 36 (33.6%) zeros Zeros
CGD AIX EN PROVENCE has 22 (20.6%) zeros Zeros
CGD ARLES has 24 (22.4%) zeros Zeros
CGD AUBAGNE has 28 (26.2%) zeros Zeros
CGD ISTRES has 31 (29.0%) zeros Zeros
CGD SALON DE PROVENCE has 20 (18.7%) zeros Zeros
CGD BAYEUX has 34 (31.8%) zeros Zeros
CGD CAEN has 33 (30.8%) zeros Zeros
CGD DEAUVILLE has 34 (31.8%) zeros Zeros
CGD FALAISE has 32 (29.9%) zeros Zeros
CGD LISIEUX has 42 (39.3%) zeros Zeros
CGD VIRE NORMANDIE has 38 (35.5%) zeros Zeros
CGD AURILLAC has 38 (35.5%) zeros Zeros
CGD MAURIAC has 46 (43.0%) zeros Zeros
CGD ST FLOUR has 42 (39.3%) zeros Zeros
CGD ANGOULEME has 34 (31.8%) zeros Zeros
CGD COGNAC has 38 (35.5%) zeros Zeros
CGD CONFOLENS has 35 (32.7%) zeros Zeros
CGD JONZAC has 27 (25.2%) zeros Zeros
CGD LA ROCHELLE has 26 (24.3%) zeros Zeros
CGD ROCHEFORT has 25 (23.4%) zeros Zeros
CGD SAINTES has 31 (29.0%) zeros Zeros
CGD ST JEAN D ANGELY has 34 (31.8%) zeros Zeros
CGD BOURGES has 35 (32.7%) zeros Zeros
CGD ST AMAND MONTROND has 37 (34.6%) zeros Zeros
CGD VIERZON has 39 (36.4%) zeros Zeros
CGD BRIVE LA GAILLARDE has 36 (33.6%) zeros Zeros
CGD USSEL has 37 (34.6%) zeros Zeros
CGD BEAUNE has 32 (29.9%) zeros Zeros
CGD DIJON has 31 (29.0%) zeros Zeros
CGD IS SUR TILLE has 41 (38.3%) zeros Zeros
CGD MONTBARD has 38 (35.5%) zeros Zeros
CGD DINAN has 33 (30.8%) zeros Zeros
CGD GUINGAMP has 30 (28.0%) zeros Zeros
CGD LANNION has 27 (25.2%) zeros Zeros
CGD ST BRIEUC has 25 (23.4%) zeros Zeros
CGD AUBUSSON has 39 (36.4%) zeros Zeros
CGD GUERET has 34 (31.8%) zeros Zeros
CGD BERGERAC has 36 (33.6%) zeros Zeros
CGD NONTRON has 38 (35.5%) zeros Zeros
CGD PERIGUEUX has 34 (31.8%) zeros Zeros
CGD SARLAT LA CANEDA has 41 (38.3%) zeros Zeros
CGD BESANCON has 24 (22.4%) zeros Zeros
CGD MONTBELIARD has 24 (22.4%) zeros Zeros
CGD PONTARLIER has 42 (39.3%) zeros Zeros
CGD CREST has 27 (25.2%) zeros Zeros
CGD NYONS has 36 (33.6%) zeros Zeros
CGD PIERRELATTE has 32 (29.9%) zeros Zeros
CGD ROMANS SUR ISERE has 23 (21.5%) zeros Zeros
CGD BERNAY has 31 (29.0%) zeros Zeros
CGD EVREUX has 25 (23.4%) zeros Zeros
CGD LES ANDELYS has 27 (25.2%) zeros Zeros
CGD LOUVIERS has 35 (32.7%) zeros Zeros
CGD PONT AUDEMER has 33 (30.8%) zeros Zeros
CGD CHATEAUDUN has 32 (29.9%) zeros Zeros
CGD DREUX has 28 (26.2%) zeros Zeros
CGD LUCE has 25 (23.4%) zeros Zeros
CGD NOGENT LE ROTROU has 37 (34.6%) zeros Zeros
CGD BREST has 29 (27.1%) zeros Zeros
CGD CHATEAULIN has 35 (32.7%) zeros Zeros
CGD LANDERNEAU has 36 (33.6%) zeros Zeros
CGD PLOURIN LES MORLAIX has 28 (26.2%) zeros Zeros
CGD QUIMPER has 24 (22.4%) zeros Zeros
CGD QUIMPERLE has 33 (30.8%) zeros Zeros
CGD AJACCIO has 38 (35.5%) zeros Zeros
CGD PORTO VECCHIO has 28 (26.2%) zeros Zeros
CGD SARTENE has 43 (40.2%) zeros Zeros
CGD BASTIA has 33 (30.8%) zeros Zeros
CGD CALVI has 39 (36.4%) zeros Zeros
CGD CORTE has 43 (40.2%) zeros Zeros
CGD GHISONACCIA has 37 (34.6%) zeros Zeros
CGD ALES has 25 (23.4%) zeros Zeros
CGD BAGNOLS SUR CEZE has 28 (26.2%) zeros Zeros
CGD LE VIGAN has 44 (41.1%) zeros Zeros
CGD NIMES has 22 (20.6%) zeros Zeros
CGD VAUVERT has 22 (20.6%) zeros Zeros
CGD MURET has 23 (21.5%) zeros Zeros
CGD ST GAUDENS has 38 (35.5%) zeros Zeros
CGD TOULOUSE MIRAIL has 24 (22.4%) zeros Zeros
CGD TOULOUSE ST MICHEL has 22 (20.6%) zeros Zeros
CGD VILLEFRANCHE DE LAURAGAIS has 28 (26.2%) zeros Zeros
CGD AUCH has 33 (30.8%) zeros Zeros
CGD CONDOM has 27 (25.2%) zeros Zeros
CGD ARCACHON has 25 (23.4%) zeros Zeros
CGD BLAYE has 24 (22.4%) zeros Zeros
CGD BOULIAC has 27 (25.2%) zeros Zeros
CGD LANGON TOULENNE has 26 (24.3%) zeros Zeros
CGD LESPARRE MEDOC has 25 (23.4%) zeros Zeros
CGD LIBOURNE has 24 (22.4%) zeros Zeros
CGD MERIGNAC has 27 (25.2%) zeros Zeros
CGD BEZIERS has 24 (22.4%) zeros Zeros
CGD CASTELNAU LE LEZ has 18 (16.8%) zeros Zeros
CGD LODEVE has 30 (28.0%) zeros Zeros
CGD LUNEL has 18 (16.8%) zeros Zeros
CGD PEZENAS has 24 (22.4%) zeros Zeros
CGD MONTFORT SUR MEU has 32 (29.9%) zeros Zeros
CGD REDON has 31 (29.0%) zeros Zeros
CGD RENNES has 25 (23.4%) zeros Zeros
CGD ST MALO has 37 (34.6%) zeros Zeros
CGD VITRE has 25 (23.4%) zeros Zeros
CGD ISSOUDUN has 38 (35.5%) zeros Zeros
CGD LA CHATRE has 38 (35.5%) zeros Zeros
CGD LE BLANC has 47 (43.9%) zeros Zeros
CGD AMBOISE has 34 (31.8%) zeros Zeros
CGD CHINON has 29 (27.1%) zeros Zeros
CGD LOCHES has 36 (33.6%) zeros Zeros
CGD TOURS has 35 (32.7%) zeros Zeros
CGD BOURGOIN JALLIEU has 21 (19.6%) zeros Zeros
CGD GRENOBLE has 25 (23.4%) zeros Zeros
CGD LA MURE has 33 (30.8%) zeros Zeros
CGD LA TOUR DU PIN has 30 (28.0%) zeros Zeros
CGD MEYLAN has 20 (18.7%) zeros Zeros
CGD ST MARCELLIN has 29 (27.1%) zeros Zeros
CGD VIENNE has 24 (22.4%) zeros Zeros
CGD DOLE has 37 (34.6%) zeros Zeros
CGD LONS LE SAUNIER has 37 (34.6%) zeros Zeros
CGD ST CLAUDE has 37 (34.6%) zeros Zeros
CGD DAX has 30 (28.0%) zeros Zeros
CGD MONT DE MARSAN has 35 (32.7%) zeros Zeros
CGD PARENTIS EN BORN has 36 (33.6%) zeros Zeros
CGD BLOIS has 34 (31.8%) zeros Zeros
CGD ROMORANTIN LANTHENAY has 27 (25.2%) zeros Zeros
CGD VENDOME has 42 (39.3%) zeros Zeros
CGD MONTBRISON has 24 (22.4%) zeros Zeros
CGD ROANNE has 29 (27.1%) zeros Zeros
CGD ST ETIENNE has 35 (32.7%) zeros Zeros
CGD BRIOUDE has 35 (32.7%) zeros Zeros
CGD LE PUY EN VELAY has 36 (33.6%) zeros Zeros
CGD YSSINGEAUX has 31 (29.0%) zeros Zeros
CGD ANCENIS ST GEREON has 37 (34.6%) zeros Zeros
CGD CHATEAUBRIANT has 35 (32.7%) zeros Zeros
CGD NANTES has 27 (25.2%) zeros Zeros
CGD PORNIC has 33 (30.8%) zeros Zeros
CGD REZE has 20 (18.7%) zeros Zeros
CGD ST NAZAIRE has 27 (25.2%) zeros Zeros
CGD GIEN has 34 (31.8%) zeros Zeros
CGD MONTARGIS has 33 (30.8%) zeros Zeros
CGD ORLEANS has 28 (26.2%) zeros Zeros
CGD PITHIVIERS has 33 (30.8%) zeros Zeros
CGD CAHORS has 42 (39.3%) zeros Zeros
CGD FIGEAC has 34 (31.8%) zeros Zeros
CGD GOURDON has 34 (31.8%) zeros Zeros
CGD AGEN has 36 (33.6%) zeros Zeros
CGD MARMANDE has 31 (29.0%) zeros Zeros
CGD VILLENEUVE SUR LOT has 42 (39.3%) zeros Zeros
CGD FLORAC TROIS RIVIERES has 54 (50.5%) zeros Zeros
CGD MENDE has 40 (37.4%) zeros Zeros
CGD ANGERS has 26 (24.3%) zeros Zeros
CGD CHOLET has 35 (32.7%) zeros Zeros
CGD SAUMUR has 29 (27.1%) zeros Zeros
CGD SEGRE EN ANJOU BLEU has 33 (30.8%) zeros Zeros
CGD AVRANCHES has 35 (32.7%) zeros Zeros
CGD CHERBOURG EN COTENTIN has 35 (32.7%) zeros Zeros
CGD COUTANCES has 34 (31.8%) zeros Zeros
CGD ST LO has 38 (35.5%) zeros Zeros
CGD CHALONS EN CHAMPAGNE has 38 (35.5%) zeros Zeros
CGD EPERNAY has 35 (32.7%) zeros Zeros
CGD REIMS has 35 (32.7%) zeros Zeros
CGD VITRY LE FRANCOIS has 31 (29.0%) zeros Zeros
CGD CHAUMONT has 47 (43.9%) zeros Zeros
CGD LANGRES has 41 (38.3%) zeros Zeros
CGD ST DIZIER has 44 (41.1%) zeros Zeros
CGD CHATEAU GONTIER SUR MAYENNE has 24 (22.4%) zeros Zeros
CGD MAYENNE has 31 (29.0%) zeros Zeros
CGD LUNEVILLE has 38 (35.5%) zeros Zeros
CGD NANCY has 30 (28.0%) zeros Zeros
CGD TOUL has 38 (35.5%) zeros Zeros
CGD VAL DE BRIEY has 39 (36.4%) zeros Zeros
CGD COMMERCY has 29 (27.1%) zeros Zeros
CGD VERDUN has 34 (31.8%) zeros Zeros
CGD LORIENT has 23 (21.5%) zeros Zeros
CGD PLOERMEL has 35 (32.7%) zeros Zeros
CGD PONTIVY has 29 (27.1%) zeros Zeros
CGD VANNES has 29 (27.1%) zeros Zeros
CGD BOULAY MOSELLE has 32 (29.9%) zeros Zeros
CGD FORBACH has 32 (29.9%) zeros Zeros
CGD METZ has 28 (26.2%) zeros Zeros
CGD SARREBOURG has 35 (32.7%) zeros Zeros
CGD SARREGUEMINES has 37 (34.6%) zeros Zeros
CGD THIONVILLE has 26 (24.3%) zeros Zeros
CGD CHATEAU CHINON VILLE has 44 (41.1%) zeros Zeros
CGD COSNE COURS SUR LOIRE has 40 (37.4%) zeros Zeros
CGD NEVERS has 34 (31.8%) zeros Zeros
CGD AVESNES SUR HELPE has 34 (31.8%) zeros Zeros
CGD CAMBRAI has 32 (29.9%) zeros Zeros
CGD DOUAI has 29 (27.1%) zeros Zeros
CGD DUNKERQUE HOYMILLE has 35 (32.7%) zeros Zeros
CGD HAZEBROUCK has 33 (30.8%) zeros Zeros
CGD LILLE has 31 (29.0%) zeros Zeros
CGD VALENCIENNES has 41 (38.3%) zeros Zeros
CGD BEAUVAIS has 33 (30.8%) zeros Zeros
CGD CHANTILLY has 27 (25.2%) zeros Zeros
CGD CLERMONT has 29 (27.1%) zeros Zeros
CGD COMPIEGNE has 27 (25.2%) zeros Zeros
CGD MERU has 26 (24.3%) zeros Zeros
CGD SENLIS has 24 (22.4%) zeros Zeros
CGD ALENCON ARGENTAN has 36 (33.6%) zeros Zeros
CGD DOMFRONT EN POIRAIE has 31 (29.0%) zeros Zeros
CGD MORTAGNE AU PERCHE has 31 (29.0%) zeros Zeros
CGD ARRAS has 32 (29.9%) zeros Zeros
CGD BETHUNE has 35 (32.7%) zeros Zeros
CGD CALAIS has 36 (33.6%) zeros Zeros
CGD ECUIRES has 35 (32.7%) zeros Zeros
CGD ST OMER has 32 (29.9%) zeros Zeros
CGD ST POL SUR TERNOISE has 37 (34.6%) zeros Zeros
CGD AMBERT has 47 (43.9%) zeros Zeros
CGD CLERMONT FERRAND has 34 (31.8%) zeros Zeros
CGD ISSOIRE has 34 (31.8%) zeros Zeros
CGD RIOM has 31 (29.0%) zeros Zeros
CGD THIERS has 37 (34.6%) zeros Zeros
CGD BAYONNE has 34 (31.8%) zeros Zeros
CGD OLORON STE MARIE has 34 (31.8%) zeros Zeros
CGD ORTHEZ has 38 (35.5%) zeros Zeros
CGD PAU has 36 (33.6%) zeros Zeros
CGD ARGELES GAZOST has 43 (40.2%) zeros Zeros
CGD BAGNERES DE BIGORRE has 37 (34.6%) zeros Zeros
CGD TARBES has 40 (37.4%) zeros Zeros
CGD CERET has 26 (24.3%) zeros Zeros
CGD PERPIGNAN has 23 (21.5%) zeros Zeros
CGD PRADES has 31 (29.0%) zeros Zeros
CGD RIVESALTES has 26 (24.3%) zeros Zeros
CGD HAGUENAU has 30 (28.0%) zeros Zeros
CGD MOLSHEIM has 33 (30.8%) zeros Zeros
CGD SAVERNE has 31 (29.0%) zeros Zeros
CGD SELESTAT has 30 (28.0%) zeros Zeros
CGD STRASBOURG has 27 (25.2%) zeros Zeros
CGD WISSEMBOURG has 40 (37.4%) zeros Zeros
CGD ALTKIRCH has 37 (34.6%) zeros Zeros
CGD COLMAR has 34 (31.8%) zeros Zeros
CGD MULHOUSE has 28 (26.2%) zeros Zeros
CGD SOULTZ GUEBWILLER has 30 (28.0%) zeros Zeros
CGD BRON has 29 (27.1%) zeros Zeros
CGD GIVORS has 26 (24.3%) zeros Zeros
CGD L ARBRESLE has 27 (25.2%) zeros Zeros
CGD LYON has 26 (24.3%) zeros Zeros
CGD VILLEFRANCHE SUR SAONE has 19 (17.8%) zeros Zeros
CGD LURE has 23 (21.5%) zeros Zeros
CGD VESOUL has 28 (26.2%) zeros Zeros
CGD AUTUN has 39 (36.4%) zeros Zeros
CGD CHALON SUR SAONE has 35 (32.7%) zeros Zeros
CGD CHAROLLES has 41 (38.3%) zeros Zeros
CGD LOUHANS has 41 (38.3%) zeros Zeros
CGD MACON has 37 (34.6%) zeros Zeros
CGD LA FLECHE has 26 (24.3%) zeros Zeros
CGD LE MANS has 23 (21.5%) zeros Zeros
CGD MAMERS has 38 (35.5%) zeros Zeros
CGD ALBERTVILLE has 32 (29.9%) zeros Zeros
CGD CHAMBERY has 27 (25.2%) zeros Zeros
CGD ST JEAN DE MAURIENNE has 36 (33.6%) zeros Zeros
CGD ANNECY has 23 (21.5%) zeros Zeros
CGD BONNEVILLE has 24 (22.4%) zeros Zeros
CGD CHAMONIX MONT BLANC has 31 (29.0%) zeros Zeros
CGD ST JULIEN EN GENEVOIS has 27 (25.2%) zeros Zeros
CGD THONON LES BAINS has 28 (26.2%) zeros Zeros
CGD DIEPPE has 37 (34.6%) zeros Zeros
CGD FECAMP has 36 (33.6%) zeros Zeros
CGD LE HAVRE has 41 (38.3%) zeros Zeros
CGD NEUFCHATEL EN BRAY has 33 (30.8%) zeros Zeros
CGD ROUEN has 30 (28.0%) zeros Zeros
CGD YVETOT has 37 (34.6%) zeros Zeros
CGD COULOMMIERS has 22 (20.6%) zeros Zeros
CGD FONTAINEBLEAU has 33 (30.8%) zeros Zeros
CGD MEAUX has 25 (23.4%) zeros Zeros
CGD MELUN has 27 (25.2%) zeros Zeros
CGD PROVINS has 32 (29.9%) zeros Zeros
CGD MANTES LA JOLIE has 22 (20.6%) zeros Zeros
CGD RAMBOUILLET has 32 (29.9%) zeros Zeros
CGD ST GERMAIN EN LAYE has 27 (25.2%) zeros Zeros
CGD BRESSUIRE has 31 (29.0%) zeros Zeros
CGD NIORT has 32 (29.9%) zeros Zeros
CGD PARTHENAY has 35 (32.7%) zeros Zeros
CGD ABBEVILLE has 33 (30.8%) zeros Zeros
CGD AMIENS has 32 (29.9%) zeros Zeros
CGD MONTDIDIER has 41 (38.3%) zeros Zeros
CGD PERONNE has 34 (31.8%) zeros Zeros
CGD ALBI has 44 (41.1%) zeros Zeros
CGD CASTRES has 30 (28.0%) zeros Zeros
CGD GAILLAC has 34 (31.8%) zeros Zeros
CGD CASTELSARRASIN has 35 (32.7%) zeros Zeros
CGD MONTAUBAN has 31 (29.0%) zeros Zeros
CGD BRIGNOLES has 27 (25.2%) zeros Zeros
CGD DRAGUIGNAN has 21 (19.6%) zeros Zeros
CGD GASSIN ST TROPEZ has 22 (20.6%) zeros Zeros
CGD HYERES has 25 (23.4%) zeros Zeros
CGD LA VALETTE DU VAR has 26 (24.3%) zeros Zeros
CGD AVIGNON has 25 (23.4%) zeros Zeros
CGD CARPENTRAS has 32 (29.9%) zeros Zeros
CGD ORANGE has 31 (29.0%) zeros Zeros
CGD PERTUIS has 29 (27.1%) zeros Zeros
CGD FONTENAY LE COMTE has 28 (26.2%) zeros Zeros
CGD LA ROCHE SUR YON has 23 (21.5%) zeros Zeros
CGD LES SABLES D OLONNE has 26 (24.3%) zeros Zeros
CGD CHATELLERAULT has 35 (32.7%) zeros Zeros
CGD MONTMORILLON has 37 (34.6%) zeros Zeros
CGD POITIERS has 30 (28.0%) zeros Zeros
CGD BELLAC has 40 (37.4%) zeros Zeros
CGD LIMOGES has 35 (32.7%) zeros Zeros
CGD ST JUNIEN has 44 (41.1%) zeros Zeros
CGD NEUFCHATEAU has 30 (28.0%) zeros Zeros
CGD REMIREMONT has 28 (26.2%) zeros Zeros
CGD ST DIE DES VOSGES has 30 (28.0%) zeros Zeros
CGD AUXERRE has 31 (29.0%) zeros Zeros
CGD AVALLON has 31 (29.0%) zeros Zeros
CGD SENS has 19 (17.8%) zeros Zeros
CGD ETAMPES has 24 (22.4%) zeros Zeros
CGD EVRY COURCOURONNES has 20 (18.7%) zeros Zeros
CGD PALAISEAU has 24 (22.4%) zeros Zeros
CGD L ISLE ADAM has 25 (23.4%) zeros Zeros
CGD MONTMORENCY has 21 (19.6%) zeros Zeros
CGD PONTOISE has 30 (28.0%) zeros Zeros
CGD LE MOULE has 19 (17.8%) zeros Zeros
CGD POINTE A PITRE has 16 (15.0%) zeros Zeros
CGD ST CLAUDE (971) has 22 (20.6%) zeros Zeros
CGD FORT DE FRANCE has 25 (23.4%) zeros Zeros
CGD LA TRINITE has 27 (25.2%) zeros Zeros
CGD LE MARIN has 20 (18.7%) zeros Zeros
CGD KOUROU has 23 (21.5%) zeros Zeros
CGD MATOURY has 15 (14.0%) zeros Zeros
CGD ST LAURENT DU MARONI has 22 (20.6%) zeros Zeros
CGD ST BENOIT has 28 (26.2%) zeros Zeros
CGD ST PAUL has 27 (25.2%) zeros Zeros
CGD ST PIERRE has 24 (22.4%) zeros Zeros
CGD ST MARTIN ST BARTHELEMY has 20 (18.7%) zeros Zeros
CGD LES ARCHIPELS PAPEETE has 38 (35.5%) zeros Zeros
CGD LES ILES DU VENT FAAA has 30 (28.0%) zeros Zeros
CGD KONE has 46 (43.0%) zeros Zeros
CGD LA FOA has 44 (41.1%) zeros Zeros
CGD NOUMEA has 27 (25.2%) zeros Zeros
CGD POINDIMIE has 49 (45.8%) zeros Zeros

Reproduction

Analysis started2021-02-18 21:38:13.052403
Analysis finished2021-02-18 21:38:16.195037
Duration3.14 seconds
Software versionpandas-profiling v2.10.0
Download configurationconfig.yaml

Variables

Code index
Real number (ℝ≥0)

UNIFORM
UNIQUE

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54
Minimum1
Maximum107
Zeros0
Zeros (%)0.0%
Memory size984.0 B
2021-02-18T22:38:16.346437image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.3
Q127.5
median54
Q380.5
95-th percentile101.7
Maximum107
Range106
Interquartile range (IQR)53

Descriptive statistics

Standard deviation31.0322413
Coefficient of variation (CV)0.5746711352
Kurtosis-1.2
Mean54
Median Absolute Deviation (MAD)27
Skewness0
Sum5778
Variance963
MonotocityStrictly increasing
2021-02-18T22:38:16.511165image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1071
 
0.9%
271
 
0.9%
291
 
0.9%
301
 
0.9%
311
 
0.9%
321
 
0.9%
331
 
0.9%
341
 
0.9%
351
 
0.9%
361
 
0.9%
Other values (97)97
90.7%
ValueCountFrequency (%)
11
0.9%
21
0.9%
31
0.9%
41
0.9%
51
0.9%
ValueCountFrequency (%)
1071
0.9%
1061
0.9%
1051
0.9%
1041
0.9%
1031
0.9%

Libellé index \ CGD
Categorical

HIGH CARDINALITY
UNIFORM

Distinct104
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size984.0 B
Index non utilisé
 
4
Tentatives homicides pour d'autres motifs
 
1
Autres infractions à la législation sur les stupéfiants
 
1
Faux documents concernant la circulation des véhicules
 
1
Vols avec armes blanches contre des particuliers à leur domicile
 
1
Other values (99)
99 

Length

Max length88
Median length40
Mean length41.87850467
Min length6

Characters and Unicode

Total characters4481
Distinct characters56
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)96.3%

Sample

1st rowRèglements de compte entre malfaireurs
2nd rowHomicides pour voler et à l'occasion de vols
3rd rowHomicides pour d'autres motifs
4th rowTentatives d'homicides pour voler et à l'occasion de vols
5th rowTentatives homicides pour d'autres motifs
ValueCountFrequency (%)
Index non utilisé4
 
3.7%
Tentatives homicides pour d'autres motifs1
 
0.9%
Autres infractions à la législation sur les stupéfiants1
 
0.9%
Faux documents concernant la circulation des véhicules1
 
0.9%
Vols avec armes blanches contre des particuliers à leur domicile1
 
0.9%
Délits des courses et des jeux1
 
0.9%
Vols de véhicules de transport avec frêt1
 
0.9%
Homicides commis contre enfants de moins de 15 ans1
 
0.9%
Vols d'automobiles1
 
0.9%
Vols violents sans arme contre des particuliers à leur domicile1
 
0.9%
Other values (94)94
87.9%
2021-02-18T22:38:16.744068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de43
 
6.5%
et32
 
4.8%
à31
 
4.7%
vols28
 
4.2%
des27
 
4.1%
autres19
 
2.9%
contre19
 
2.9%
la15
 
2.3%
ou11
 
1.7%
délits9
 
1.4%
Other values (232)426
64.5%

Most occurring characters

ValueCountFrequency (%)
557
12.4%
e484
 
10.8%
s434
 
9.7%
t300
 
6.7%
i298
 
6.7%
r257
 
5.7%
n256
 
5.7%
a254
 
5.7%
o231
 
5.2%
l199
 
4.4%
Other values (46)1211
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3764
84.0%
Space Separator557
 
12.4%
Uppercase Letter108
 
2.4%
Other Punctuation39
 
0.9%
Open Punctuation4
 
0.1%
Close Punctuation4
 
0.1%
Decimal Number3
 
0.1%
Dash Punctuation2
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
e484
12.9%
s434
11.5%
t300
 
8.0%
i298
 
7.9%
r257
 
6.8%
n256
 
6.8%
a254
 
6.7%
o231
 
6.1%
l199
 
5.3%
u192
 
5.1%
Other values (19)859
22.8%
ValueCountFrequency (%)
V25
23.1%
A23
21.3%
I10
 
9.3%
C8
 
7.4%
F8
 
7.4%
D6
 
5.6%
H5
 
4.6%
P5
 
4.6%
T4
 
3.7%
M3
 
2.8%
Other values (7)11
10.2%
ValueCountFrequency (%)
'29
74.4%
,8
 
20.5%
.2
 
5.1%
ValueCountFrequency (%)
21
33.3%
11
33.3%
51
33.3%
ValueCountFrequency (%)
557
100.0%
ValueCountFrequency (%)
(4
100.0%
ValueCountFrequency (%)
)4
100.0%
ValueCountFrequency (%)
-2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3872
86.4%
Common609
 
13.6%

Most frequent character per script

ValueCountFrequency (%)
e484
12.5%
s434
11.2%
t300
 
7.7%
i298
 
7.7%
r257
 
6.6%
n256
 
6.6%
a254
 
6.6%
o231
 
6.0%
l199
 
5.1%
u192
 
5.0%
Other values (36)967
25.0%
ValueCountFrequency (%)
557
91.5%
'29
 
4.8%
,8
 
1.3%
(4
 
0.7%
)4
 
0.7%
.2
 
0.3%
-2
 
0.3%
21
 
0.2%
11
 
0.2%
51
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII4348
97.0%
None133
 
3.0%

Most frequent character per block

ValueCountFrequency (%)
557
12.8%
e484
11.1%
s434
10.0%
t300
 
6.9%
i298
 
6.9%
r257
 
5.9%
n256
 
5.9%
a254
 
5.8%
o231
 
5.3%
l199
 
4.6%
Other values (40)1078
24.8%
ValueCountFrequency (%)
é86
64.7%
à31
 
23.3%
è9
 
6.8%
ê4
 
3.0%
ç2
 
1.5%
î1
 
0.8%

CGD BELLEY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean32.40776699
Minimum0
Maximum384
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:38:16.845818image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q333.5
95-th percentile154.9
Maximum384
Range384
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation62.25885824
Coefficient of variation (CV)1.921109167
Kurtosis11.67560625
Mean32.40776699
Median Absolute Deviation (MAD)4
Skewness3.112302519
Sum3338
Variance3876.165429
MonotocityNot monotonic
2021-02-18T22:38:16.944519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
031
29.0%
27
 
6.5%
17
 
6.5%
54
 
3.7%
44
 
3.7%
34
 
3.7%
233
 
2.8%
202
 
1.9%
1052
 
1.9%
162
 
1.9%
Other values (34)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
17
 
6.5%
27
 
6.5%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
3841
0.9%
2591
0.9%
2251
0.9%
2061
0.9%
1791
0.9%

CGD BOURG EN BRESSE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct53
Distinct (%)51.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean41.81553398
Minimum0
Maximum493
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:38:17.047232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q341
95-th percentile202.9
Maximum493
Range493
Interquartile range (IQR)41

Descriptive statistics

Standard deviation78.25407934
Coefficient of variation (CV)1.871411695
Kurtosis11.89932277
Mean41.81553398
Median Absolute Deviation (MAD)7
Skewness3.075206409
Sum4307
Variance6123.700933
MonotocityNot monotonic
2021-02-18T22:38:17.149826image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
029
27.1%
110
 
9.3%
24
 
3.7%
34
 
3.7%
53
 
2.8%
152
 
1.9%
242
 
1.9%
102
 
1.9%
132
 
1.9%
72
 
1.9%
Other values (43)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
110
 
9.3%
24
 
3.7%
34
 
3.7%
41
 
0.9%
ValueCountFrequency (%)
4931
0.9%
3011
0.9%
2951
0.9%
2261
0.9%
2131
0.9%

CGD GEX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean51.76699029
Minimum0
Maximum588
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:38:17.248849image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median10
Q349.5
95-th percentile273.8
Maximum588
Range588
Interquartile range (IQR)49

Descriptive statistics

Standard deviation104.3578124
Coefficient of variation (CV)2.015914231
Kurtosis12.58267881
Mean51.76699029
Median Absolute Deviation (MAD)10
Skewness3.301038586
Sum5332
Variance10890.55302
MonotocityNot monotonic
2021-02-18T22:38:17.345564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
026
24.3%
17
 
6.5%
27
 
6.5%
35
 
4.7%
104
 
3.7%
114
 
3.7%
42
 
1.9%
332
 
1.9%
182
 
1.9%
572
 
1.9%
Other values (39)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
17
 
6.5%
27
 
6.5%
35
 
4.7%
42
 
1.9%
ValueCountFrequency (%)
5881
0.9%
5741
0.9%
3591
0.9%
3121
0.9%
2931
0.9%

CGD TREVOUX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct53
Distinct (%)51.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean58.25242718
Minimum0
Maximum682
Zeros19
Zeros (%)17.8%
Memory size984.0 B
2021-02-18T22:38:17.447604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q344.5
95-th percentile275.4
Maximum682
Range682
Interquartile range (IQR)43.5

Descriptive statistics

Standard deviation118.7065684
Coefficient of variation (CV)2.037796091
Kurtosis11.40311999
Mean58.25242718
Median Absolute Deviation (MAD)7
Skewness3.186524008
Sum6000
Variance14091.24938
MonotocityNot monotonic
2021-02-18T22:38:17.670243image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
019
17.8%
111
 
10.3%
59
 
8.4%
26
 
5.6%
33
 
2.8%
73
 
2.8%
242
 
1.9%
262
 
1.9%
1482
 
1.9%
42
 
1.9%
Other values (43)44
41.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
019
17.8%
111
10.3%
26
 
5.6%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
6821
0.9%
5791
0.9%
4631
0.9%
3911
0.9%
3381
0.9%

CGD CHATEAU THIERRY NOGENTEL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.91262136
Minimum0
Maximum165
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:17.780361image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314.5
95-th percentile82
Maximum165
Range165
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation32.5034257
Coefficient of variation (CV)1.921844344
Kurtosis7.569781405
Mean16.91262136
Median Absolute Deviation (MAD)2
Skewness2.690552991
Sum1742
Variance1056.472682
MonotocityNot monotonic
2021-02-18T22:38:17.868196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
037
34.6%
112
 
11.2%
27
 
6.5%
74
 
3.7%
822
 
1.9%
162
 
1.9%
102
 
1.9%
142
 
1.9%
312
 
1.9%
62
 
1.9%
Other values (27)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
112
 
11.2%
27
 
6.5%
32
 
1.9%
41
 
0.9%
ValueCountFrequency (%)
1651
0.9%
1481
0.9%
1401
0.9%
921
0.9%
861
0.9%

CGD LAON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean36.68932039
Minimum0
Maximum331
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:17.964642image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q333
95-th percentile175
Maximum331
Range331
Interquartile range (IQR)33

Descriptive statistics

Standard deviation69.64279014
Coefficient of variation (CV)1.898176074
Kurtosis7.168422999
Mean36.68932039
Median Absolute Deviation (MAD)4
Skewness2.675204773
Sum3779
Variance4850.118218
MonotocityNot monotonic
2021-02-18T22:38:18.058587image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
028
26.2%
111
 
10.3%
25
 
4.7%
45
 
4.7%
33
 
2.8%
173
 
2.8%
143
 
2.8%
332
 
1.9%
312
 
1.9%
52
 
1.9%
Other values (36)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
111
 
10.3%
25
 
4.7%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
3311
0.9%
3231
0.9%
2881
0.9%
2621
0.9%
2201
0.9%

CGD SOISSONS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean24.31067961
Minimum0
Maximum260
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:18.152159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q321.5
95-th percentile118.9
Maximum260
Range260
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation46.97392458
Coefficient of variation (CV)1.932234118
Kurtosis8.859610256
Mean24.31067961
Median Absolute Deviation (MAD)5
Skewness2.859024459
Sum2504
Variance2206.549591
MonotocityNot monotonic
2021-02-18T22:38:18.246918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
27
 
6.5%
125
 
4.7%
64
 
3.7%
54
 
3.7%
142
 
1.9%
72
 
1.9%
372
 
1.9%
202
 
1.9%
Other values (29)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
27
 
6.5%
42
 
1.9%
54
 
3.7%
ValueCountFrequency (%)
2601
0.9%
2061
0.9%
1761
0.9%
1711
0.9%
1301
0.9%

CGD ST QUENTIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.09708738
Minimum0
Maximum212
Zeros39
Zeros (%)36.4%
Memory size984.0 B
2021-02-18T22:38:18.341454image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q322.5
95-th percentile103.7
Maximum212
Range212
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation40.8427195
Coefficient of variation (CV)1.848330452
Kurtosis7.201537103
Mean22.09708738
Median Absolute Deviation (MAD)3
Skewness2.607508687
Sum2276
Variance1668.127737
MonotocityNot monotonic
2021-02-18T22:38:18.430944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
039
36.4%
36
 
5.6%
16
 
5.6%
24
 
3.7%
153
 
2.8%
112
 
1.9%
122
 
1.9%
102
 
1.9%
42
 
1.9%
72
 
1.9%
Other values (31)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
039
36.4%
16
 
5.6%
24
 
3.7%
36
 
5.6%
42
 
1.9%
ValueCountFrequency (%)
2121
0.9%
1811
0.9%
1651
0.9%
1301
0.9%
1181
0.9%

CGD VERVINS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.18446602
Minimum0
Maximum213
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:18.525808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q329.5
95-th percentile126.1
Maximum213
Range213
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation39.61821416
Coefficient of variation (CV)1.785853855
Kurtosis7.704664692
Mean22.18446602
Median Absolute Deviation (MAD)4
Skewness2.670767734
Sum2285
Variance1569.602894
MonotocityNot monotonic
2021-02-18T22:38:18.616027image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
036
33.6%
18
 
7.5%
46
 
5.6%
25
 
4.7%
53
 
2.8%
363
 
2.8%
32
 
1.9%
102
 
1.9%
152
 
1.9%
282
 
1.9%
Other values (33)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
18
 
7.5%
25
 
4.7%
32
 
1.9%
46
 
5.6%
ValueCountFrequency (%)
2131
0.9%
1701
0.9%
1471
0.9%
1351
0.9%
1291
0.9%

CGD MONTLUCON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct33
Distinct (%)32.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.01941748
Minimum0
Maximum162
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:18.704242image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310
95-th percentile57.7
Maximum162
Range162
Interquartile range (IQR)10

Descriptive statistics

Standard deviation24.90136644
Coefficient of variation (CV)2.071761505
Kurtosis15.33397009
Mean12.01941748
Median Absolute Deviation (MAD)2
Skewness3.550321532
Sum1238
Variance620.0780506
MonotocityNot monotonic
2021-02-18T22:38:18.792286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
037
34.6%
112
 
11.2%
26
 
5.6%
55
 
4.7%
34
 
3.7%
173
 
2.8%
73
 
2.8%
63
 
2.8%
93
 
2.8%
42
 
1.9%
Other values (23)25
23.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
112
 
11.2%
26
 
5.6%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
1621
0.9%
1131
0.9%
921
0.9%
641
0.9%
621
0.9%

CGD MOULINS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.94174757
Minimum0
Maximum149
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:38:18.888730image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314.5
95-th percentile64.7
Maximum149
Range149
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation24.6846087
Coefficient of variation (CV)1.907362863
Kurtosis10.75338423
Mean12.94174757
Median Absolute Deviation (MAD)2
Skewness3.020187595
Sum1333
Variance609.3299067
MonotocityNot monotonic
2021-02-18T22:38:18.977521image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
038
35.5%
28
 
7.5%
18
 
7.5%
45
 
4.7%
54
 
3.7%
83
 
2.8%
33
 
2.8%
92
 
1.9%
242
 
1.9%
62
 
1.9%
Other values (27)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
18
 
7.5%
28
 
7.5%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
1491
0.9%
981
0.9%
901
0.9%
891
0.9%
661
0.9%

CGD VICHY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.13592233
Minimum0
Maximum336
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:19.074083image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q326
95-th percentile115.8
Maximum336
Range336
Interquartile range (IQR)26

Descriptive statistics

Standard deviation50.28468923
Coefficient of variation (CV)2.000511005
Kurtosis15.9566731
Mean25.13592233
Median Absolute Deviation (MAD)3
Skewness3.54248735
Sum2589
Variance2528.549971
MonotocityNot monotonic
2021-02-18T22:38:19.316231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
035
32.7%
110
 
9.3%
34
 
3.7%
114
 
3.7%
43
 
2.8%
243
 
2.8%
23
 
2.8%
472
 
1.9%
92
 
1.9%
142
 
1.9%
Other values (33)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
110
 
9.3%
23
 
2.8%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
3361
0.9%
2201
0.9%
1611
0.9%
1431
0.9%
1341
0.9%

CGD BARCELONNETTE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct21
Distinct (%)20.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean5.077669903
Minimum0
Maximum77
Zeros52
Zeros (%)48.6%
Memory size984.0 B
2021-02-18T22:38:19.408811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile26.7
Maximum77
Range77
Interquartile range (IQR)4

Descriptive statistics

Standard deviation11.9694786
Coefficient of variation (CV)2.357277813
Kurtosis16.19987036
Mean5.077669903
Median Absolute Deviation (MAD)0
Skewness3.78449155
Sum523
Variance143.268418
MonotocityNot monotonic
2021-02-18T22:38:19.489124image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
052
48.6%
210
 
9.3%
18
 
7.5%
35
 
4.7%
45
 
4.7%
53
 
2.8%
492
 
1.9%
132
 
1.9%
92
 
1.9%
72
 
1.9%
Other values (11)12
 
11.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
052
48.6%
18
 
7.5%
210
 
9.3%
35
 
4.7%
45
 
4.7%
ValueCountFrequency (%)
771
0.9%
492
1.9%
461
0.9%
321
0.9%
271
0.9%

CGD CASTELLANE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct27
Distinct (%)26.2%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean8.650485437
Minimum0
Maximum106
Zeros48
Zeros (%)44.9%
Memory size984.0 B
2021-02-18T22:38:19.586786image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q37
95-th percentile59.2
Maximum106
Range106
Interquartile range (IQR)7

Descriptive statistics

Standard deviation18.64409108
Coefficient of variation (CV)2.155265299
Kurtosis10.43434817
Mean8.650485437
Median Absolute Deviation (MAD)1
Skewness3.133002007
Sum891
Variance347.6021321
MonotocityNot monotonic
2021-02-18T22:38:19.683050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
048
44.9%
114
 
13.1%
45
 
4.7%
53
 
2.8%
63
 
2.8%
112
 
1.9%
22
 
1.9%
32
 
1.9%
432
 
1.9%
232
 
1.9%
Other values (17)20
18.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
048
44.9%
114
 
13.1%
22
 
1.9%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
1061
0.9%
801
0.9%
681
0.9%
641
0.9%
631
0.9%

CGD DIGNE LES BAINS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.33980583
Minimum0
Maximum206
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:19.784062image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q312.5
95-th percentile101.6
Maximum206
Range206
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation37.78591744
Coefficient of variation (CV)2.179143055
Kurtosis11.20366823
Mean17.33980583
Median Absolute Deviation (MAD)2
Skewness3.273805174
Sum1786
Variance1427.775557
MonotocityNot monotonic
2021-02-18T22:38:19.880793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
034
31.8%
113
 
12.1%
28
 
7.5%
84
 
3.7%
103
 
2.8%
243
 
2.8%
93
 
2.8%
52
 
1.9%
122
 
1.9%
42
 
1.9%
Other values (26)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
113
 
12.1%
28
 
7.5%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
2061
0.9%
1861
0.9%
1601
0.9%
1201
0.9%
1121
0.9%

CGD FORCALQUIER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean18.15533981
Minimum0
Maximum228
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:19.976723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314
95-th percentile106.6
Maximum228
Range228
Interquartile range (IQR)14

Descriptive statistics

Standard deviation37.7800023
Coefficient of variation (CV)2.080930608
Kurtosis11.34598089
Mean18.15533981
Median Absolute Deviation (MAD)2
Skewness3.172923266
Sum1870
Variance1427.328574
MonotocityNot monotonic
2021-02-18T22:38:20.074020image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
035
32.7%
113
 
12.1%
65
 
4.7%
34
 
3.7%
24
 
3.7%
133
 
2.8%
103
 
2.8%
53
 
2.8%
72
 
1.9%
182
 
1.9%
Other values (24)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
113
 
12.1%
24
 
3.7%
34
 
3.7%
53
 
2.8%
ValueCountFrequency (%)
2281
0.9%
1441
0.9%
1411
0.9%
1311
0.9%
1201
0.9%

CGD BRIANCON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct31
Distinct (%)30.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean14.37864078
Minimum0
Maximum203
Zeros42
Zeros (%)39.3%
Memory size984.0 B
2021-02-18T22:38:20.171752image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310.5
95-th percentile63.4
Maximum203
Range203
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation34.80312035
Coefficient of variation (CV)2.420473597
Kurtosis16.52670815
Mean14.37864078
Median Absolute Deviation (MAD)2
Skewness3.944022518
Sum1481
Variance1211.257186
MonotocityNot monotonic
2021-02-18T22:38:20.264601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
042
39.3%
17
 
6.5%
26
 
5.6%
75
 
4.7%
64
 
3.7%
54
 
3.7%
133
 
2.8%
103
 
2.8%
43
 
2.8%
202
 
1.9%
Other values (21)24
22.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
042
39.3%
17
 
6.5%
26
 
5.6%
31
 
0.9%
43
 
2.8%
ValueCountFrequency (%)
2031
0.9%
1811
0.9%
1711
0.9%
1041
0.9%
991
0.9%

CGD GAP
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.90291262
Minimum0
Maximum209
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:20.366510image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q314
95-th percentile104
Maximum209
Range209
Interquartile range (IQR)14

Descriptive statistics

Standard deviation36.94577759
Coefficient of variation (CV)2.185763981
Kurtosis12.42601544
Mean16.90291262
Median Absolute Deviation (MAD)3
Skewness3.445896722
Sum1741
Variance1364.990482
MonotocityNot monotonic
2021-02-18T22:38:20.480777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
033
30.8%
19
 
8.4%
37
 
6.5%
26
 
5.6%
95
 
4.7%
214
 
3.7%
144
 
3.7%
43
 
2.8%
73
 
2.8%
62
 
1.9%
Other values (24)27
25.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
19
 
8.4%
26
 
5.6%
37
 
6.5%
43
 
2.8%
ValueCountFrequency (%)
2091
0.9%
1801
0.9%
1531
0.9%
1361
0.9%
1052
1.9%

CGD CANNES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct53
Distinct (%)51.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean62.24271845
Minimum0
Maximum789
Zeros20
Zeros (%)18.7%
Memory size984.0 B
2021-02-18T22:38:20.609031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median12
Q358
95-th percentile323.4
Maximum789
Range789
Interquartile range (IQR)57

Descriptive statistics

Standard deviation129.1641656
Coefficient of variation (CV)2.075169094
Kurtosis13.24865784
Mean62.24271845
Median Absolute Deviation (MAD)12
Skewness3.441704835
Sum6411
Variance16683.38169
MonotocityNot monotonic
2021-02-18T22:38:20.720572image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
020
18.7%
112
 
11.2%
85
 
4.7%
23
 
2.8%
33
 
2.8%
93
 
2.8%
173
 
2.8%
113
 
2.8%
122
 
1.9%
802
 
1.9%
Other values (43)47
43.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
020
18.7%
112
11.2%
23
 
2.8%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
7891
0.9%
5951
0.9%
4761
0.9%
4371
0.9%
4271
0.9%

CGD GRASSE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean29.78640777
Minimum0
Maximum453
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:20.827630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q331
95-th percentile174
Maximum453
Range453
Interquartile range (IQR)31

Descriptive statistics

Standard deviation64.25358012
Coefficient of variation (CV)2.157144313
Kurtosis19.5151823
Mean29.78640777
Median Absolute Deviation (MAD)5
Skewness3.91906014
Sum3068
Variance4128.522559
MonotocityNot monotonic
2021-02-18T22:38:20.929595image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
028
26.2%
29
 
8.4%
45
 
4.7%
15
 
4.7%
94
 
3.7%
313
 
2.8%
33
 
2.8%
83
 
2.8%
53
 
2.8%
233
 
2.8%
Other values (30)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
15
 
4.7%
29
 
8.4%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
4531
0.9%
2251
0.9%
2161
0.9%
2051
0.9%
1831
0.9%

CGD MENTON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean15.2815534
Minimum0
Maximum175
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:38:21.067518image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q312
95-th percentile83.3
Maximum175
Range175
Interquartile range (IQR)12

Descriptive statistics

Standard deviation30.8155224
Coefficient of variation (CV)2.016517667
Kurtosis9.783558503
Mean15.2815534
Median Absolute Deviation (MAD)3
Skewness3.019320205
Sum1574
Variance949.5964211
MonotocityNot monotonic
2021-02-18T22:38:21.194977image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
031
29.0%
114
13.1%
26
 
5.6%
65
 
4.7%
35
 
4.7%
104
 
3.7%
163
 
2.8%
93
 
2.8%
53
 
2.8%
742
 
1.9%
Other values (24)27
25.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
114
13.1%
26
 
5.6%
35
 
4.7%
42
 
1.9%
ValueCountFrequency (%)
1751
0.9%
1361
0.9%
1111
0.9%
1021
0.9%
961
0.9%

CGD NICE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean32.30097087
Minimum0
Maximum352
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:21.335555image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q328
95-th percentile178.3
Maximum352
Range352
Interquartile range (IQR)28

Descriptive statistics

Standard deviation61.30873893
Coefficient of variation (CV)1.898046321
Kurtosis9.483469004
Mean32.30097087
Median Absolute Deviation (MAD)7
Skewness2.93998818
Sum3327
Variance3758.76147
MonotocityNot monotonic
2021-02-18T22:38:21.457492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
028
26.2%
18
 
7.5%
37
 
6.5%
144
 
3.7%
44
 
3.7%
283
 
2.8%
173
 
2.8%
292
 
1.9%
222
 
1.9%
132
 
1.9%
Other values (35)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
18
 
7.5%
22
 
1.9%
37
 
6.5%
44
 
3.7%
ValueCountFrequency (%)
3521
0.9%
2641
0.9%
2191
0.9%
1911
0.9%
1841
0.9%

CGD PUGET THENIERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct28
Distinct (%)27.2%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean10.03883495
Minimum0
Maximum122
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:21.565627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310.5
95-th percentile47.7
Maximum122
Range122
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation20.43014033
Coefficient of variation (CV)2.035110691
Kurtosis13.26508041
Mean10.03883495
Median Absolute Deviation (MAD)2
Skewness3.461833974
Sum1034
Variance417.3906339
MonotocityNot monotonic
2021-02-18T22:38:21.892139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
037
34.6%
110
 
9.3%
36
 
5.6%
65
 
4.7%
45
 
4.7%
25
 
4.7%
94
 
3.7%
154
 
3.7%
164
 
3.7%
122
 
1.9%
Other values (18)21
19.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
110
 
9.3%
25
 
4.7%
36
 
5.6%
45
 
4.7%
ValueCountFrequency (%)
1221
0.9%
951
0.9%
901
0.9%
721
0.9%
531
0.9%

CGD LARGENTIERE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.91262136
Minimum0
Maximum444
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:22.025248image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q319.5
95-th percentile152.9
Maximum444
Range444
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation63.47488415
Coefficient of variation (CV)2.274056719
Kurtosis19.95932713
Mean27.91262136
Median Absolute Deviation (MAD)3
Skewness3.998009957
Sum2875
Variance4029.060918
MonotocityNot monotonic
2021-02-18T22:38:22.150088image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
036
33.6%
110
 
9.3%
24
 
3.7%
84
 
3.7%
144
 
3.7%
63
 
2.8%
162
 
1.9%
92
 
1.9%
212
 
1.9%
32
 
1.9%
Other values (29)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
110
 
9.3%
24
 
3.7%
32
 
1.9%
41
 
0.9%
ValueCountFrequency (%)
4441
0.9%
2751
0.9%
1911
0.9%
1801
0.9%
1771
0.9%

CGD LE TEIL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean30.39805825
Minimum0
Maximum279
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:38:22.260782image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q328
95-th percentile153
Maximum279
Range279
Interquartile range (IQR)28

Descriptive statistics

Standard deviation56.51502313
Coefficient of variation (CV)1.859165564
Kurtosis6.413100092
Mean30.39805825
Median Absolute Deviation (MAD)5
Skewness2.530005227
Sum3131
Variance3193.947839
MonotocityNot monotonic
2021-02-18T22:38:22.347115image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
029
27.1%
112
 
11.2%
25
 
4.7%
44
 
3.7%
103
 
2.8%
283
 
2.8%
83
 
2.8%
173
 
2.8%
53
 
2.8%
72
 
1.9%
Other values (32)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
112
11.2%
25
 
4.7%
31
 
0.9%
44
 
3.7%
ValueCountFrequency (%)
2791
0.9%
2441
0.9%
2311
0.9%
1981
0.9%
1621
0.9%

CGD TOURNON SUR RHONE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean32.89320388
Minimum0
Maximum460
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:22.438648image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q329
95-th percentile146.6
Maximum460
Range460
Interquartile range (IQR)29

Descriptive statistics

Standard deviation65.76948941
Coefficient of variation (CV)1.999485658
Kurtosis18.61829769
Mean32.89320388
Median Absolute Deviation (MAD)5
Skewness3.776756255
Sum3388
Variance4325.625738
MonotocityNot monotonic
2021-02-18T22:38:22.532509image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
027
25.2%
110
 
9.3%
45
 
4.7%
134
 
3.7%
34
 
3.7%
53
 
2.8%
173
 
2.8%
23
 
2.8%
113
 
2.8%
252
 
1.9%
Other values (34)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
110
 
9.3%
23
 
2.8%
34
 
3.7%
45
 
4.7%
ValueCountFrequency (%)
4601
0.9%
2611
0.9%
2331
0.9%
1891
0.9%
1731
0.9%
Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size984.0 B
0.0
103 
nan
 
4

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters321
Distinct characters4
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0
ValueCountFrequency (%)
0.0103
96.3%
nan4
 
3.7%
2021-02-18T22:38:22.691823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-02-18T22:38:22.752913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0103
96.3%
nan4
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0206
64.2%
.103
32.1%
n8
 
2.5%
a4
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number206
64.2%
Other Punctuation103
32.1%
Lowercase Letter12
 
3.7%

Most frequent character per category

ValueCountFrequency (%)
n8
66.7%
a4
33.3%
ValueCountFrequency (%)
0206
100.0%
ValueCountFrequency (%)
.103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common309
96.3%
Latin12
 
3.7%

Most frequent character per script

ValueCountFrequency (%)
0206
66.7%
.103
33.3%
ValueCountFrequency (%)
n8
66.7%
a4
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII321
100.0%

Most frequent character per block

ValueCountFrequency (%)
0206
64.2%
.103
32.1%
n8
 
2.5%
a4
 
1.2%

CGD RETHEL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.82524272
Minimum0
Maximum113
Zeros39
Zeros (%)36.4%
Memory size984.0 B
2021-02-18T22:38:22.818695image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q315
95-th percentile53.1
Maximum113
Range113
Interquartile range (IQR)15

Descriptive statistics

Standard deviation23.20092425
Coefficient of variation (CV)1.809004692
Kurtosis7.662850595
Mean12.82524272
Median Absolute Deviation (MAD)2
Skewness2.664554361
Sum1321
Variance538.282886
MonotocityNot monotonic
2021-02-18T22:38:22.904303image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
039
36.4%
112
 
11.2%
85
 
4.7%
45
 
4.7%
25
 
4.7%
33
 
2.8%
152
 
1.9%
272
 
1.9%
422
 
1.9%
132
 
1.9%
Other values (26)26
24.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
039
36.4%
112
 
11.2%
25
 
4.7%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
1131
0.9%
1121
0.9%
961
0.9%
921
0.9%
591
0.9%

CGD REVIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.52427184
Minimum0
Maximum237
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:22.991641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q316
95-th percentile97
Maximum237
Range237
Interquartile range (IQR)16

Descriptive statistics

Standard deviation38.78797182
Coefficient of variation (CV)1.986653952
Kurtosis11.80228998
Mean19.52427184
Median Absolute Deviation (MAD)3
Skewness3.14153078
Sum2011
Variance1504.506758
MonotocityNot monotonic
2021-02-18T22:38:23.080691image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
033
30.8%
114
13.1%
36
 
5.6%
124
 
3.7%
93
 
2.8%
43
 
2.8%
73
 
2.8%
62
 
1.9%
82
 
1.9%
22
 
1.9%
Other values (28)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
114
13.1%
22
 
1.9%
36
 
5.6%
43
 
2.8%
ValueCountFrequency (%)
2371
0.9%
1731
0.9%
1421
0.9%
1111
0.9%
1021
0.9%

CGD SEDAN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.14563107
Minimum0
Maximum388
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:23.173283image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q324
95-th percentile131.8
Maximum388
Range388
Interquartile range (IQR)24

Descriptive statistics

Standard deviation57.84994242
Coefficient of variation (CV)2.131095876
Kurtosis17.83826108
Mean27.14563107
Median Absolute Deviation (MAD)4
Skewness3.793204636
Sum2796
Variance3346.615839
MonotocityNot monotonic
2021-02-18T22:38:23.270168image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
35
 
4.7%
44
 
3.7%
24
 
3.7%
73
 
2.8%
243
 
2.8%
123
 
2.8%
143
 
2.8%
52
 
1.9%
Other values (31)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
24
 
3.7%
35
 
4.7%
44
 
3.7%
ValueCountFrequency (%)
3881
0.9%
2841
0.9%
1721
0.9%
1481
0.9%
1421
0.9%

CGD VOUZIERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct29
Distinct (%)28.2%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean7
Minimum0
Maximum86
Zeros51
Zeros (%)47.7%
Memory size984.0 B
2021-02-18T22:38:23.371469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q37.5
95-th percentile31.8
Maximum86
Range86
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation14.03916092
Coefficient of variation (CV)2.005594417
Kurtosis11.91051092
Mean7
Median Absolute Deviation (MAD)1
Skewness3.165121459
Sum721
Variance197.0980392
MonotocityNot monotonic
2021-02-18T22:38:23.485964image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
051
47.7%
26
 
5.6%
36
 
5.6%
16
 
5.6%
44
 
3.7%
182
 
1.9%
102
 
1.9%
52
 
1.9%
172
 
1.9%
82
 
1.9%
Other values (19)20
 
18.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
051
47.7%
16
 
5.6%
26
 
5.6%
36
 
5.6%
44
 
3.7%
ValueCountFrequency (%)
861
0.9%
571
0.9%
531
0.9%
521
0.9%
381
0.9%

CGD FOIX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean15.19417476
Minimum0
Maximum192
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:23.606340image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q315.5
95-th percentile77.2
Maximum192
Range192
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation30.70034114
Coefficient of variation (CV)2.020533634
Kurtosis13.26516798
Mean15.19417476
Median Absolute Deviation (MAD)2
Skewness3.347013886
Sum1565
Variance942.5109461
MonotocityNot monotonic
2021-02-18T22:38:23.732005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
036
33.6%
111
 
10.3%
25
 
4.7%
84
 
3.7%
74
 
3.7%
164
 
3.7%
33
 
2.8%
223
 
2.8%
63
 
2.8%
92
 
1.9%
Other values (24)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
111
 
10.3%
25
 
4.7%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
1921
0.9%
1401
0.9%
1031
0.9%
991
0.9%
871
0.9%

CGD PAMIERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean18.82524272
Minimum0
Maximum218
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:23.840101image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q321
95-th percentile91.9
Maximum218
Range218
Interquartile range (IQR)21

Descriptive statistics

Standard deviation37.26282571
Coefficient of variation (CV)1.979407451
Kurtosis12.58084379
Mean18.82524272
Median Absolute Deviation (MAD)3
Skewness3.262528534
Sum1939
Variance1388.51818
MonotocityNot monotonic
2021-02-18T22:38:23.963465image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
033
30.8%
112
 
11.2%
26
 
5.6%
75
 
4.7%
34
 
3.7%
43
 
2.8%
103
 
2.8%
343
 
2.8%
62
 
1.9%
222
 
1.9%
Other values (26)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
112
 
11.2%
26
 
5.6%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
2181
0.9%
1991
0.9%
1121
0.9%
1101
0.9%
931
0.9%

CGD ST GIRONS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct28
Distinct (%)27.2%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean10.27184466
Minimum0
Maximum105
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:24.086221image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q311
95-th percentile50.1
Maximum105
Range105
Interquartile range (IQR)11

Descriptive statistics

Standard deviation19.61651674
Coefficient of variation (CV)1.909736507
Kurtosis10.50762934
Mean10.27184466
Median Absolute Deviation (MAD)2
Skewness3.093922527
Sum1058
Variance384.8077289
MonotocityNot monotonic
2021-02-18T22:38:24.208603image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
035
32.7%
115
14.0%
35
 
4.7%
94
 
3.7%
24
 
3.7%
54
 
3.7%
44
 
3.7%
213
 
2.8%
133
 
2.8%
83
 
2.8%
Other values (18)23
21.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
115
14.0%
24
 
3.7%
35
 
4.7%
44
 
3.7%
ValueCountFrequency (%)
1051
0.9%
1021
0.9%
771
0.9%
661
0.9%
621
0.9%

CGD BAR SUR AUBE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.02912621
Minimum0
Maximum165
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:24.311826image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q318.5
95-th percentile102.2
Maximum165
Range165
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation35.43108647
Coefficient of variation (CV)1.768978142
Kurtosis5.32331082
Mean20.02912621
Median Absolute Deviation (MAD)3
Skewness2.342247356
Sum2063
Variance1255.361888
MonotocityNot monotonic
2021-02-18T22:38:24.421630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
033
30.8%
19
 
8.4%
29
 
8.4%
64
 
3.7%
34
 
3.7%
84
 
3.7%
53
 
2.8%
172
 
1.9%
102
 
1.9%
162
 
1.9%
Other values (30)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
19
 
8.4%
29
 
8.4%
34
 
3.7%
53
 
2.8%
ValueCountFrequency (%)
1651
0.9%
1551
0.9%
1401
0.9%
1181
0.9%
1131
0.9%

CGD NOGENT SUR SEINE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.52427184
Minimum0
Maximum273
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:38:24.553958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q328.5
95-th percentile153.5
Maximum273
Range273
Interquartile range (IQR)28.5

Descriptive statistics

Standard deviation53.65792975
Coefficient of variation (CV)1.881132323
Kurtosis6.868192819
Mean28.52427184
Median Absolute Deviation (MAD)4
Skewness2.604623449
Sum2938
Variance2879.173425
MonotocityNot monotonic
2021-02-18T22:38:24.677802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
031
29.0%
18
 
7.5%
27
 
6.5%
46
 
5.6%
64
 
3.7%
532
 
1.9%
322
 
1.9%
132
 
1.9%
112
 
1.9%
32
 
1.9%
Other values (36)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
18
 
7.5%
27
 
6.5%
32
 
1.9%
46
 
5.6%
ValueCountFrequency (%)
2731
0.9%
2401
0.9%
2041
0.9%
1601
0.9%
1591
0.9%

CGD ROSIERES PRES TROYES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.45631068
Minimum0
Maximum308
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:25.076436image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q326.5
95-th percentile123.9
Maximum308
Range308
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation54.91968766
Coefficient of variation (CV)1.929965141
Kurtosis10.51755817
Mean28.45631068
Median Absolute Deviation (MAD)4
Skewness3.056147946
Sum2931
Variance3016.172092
MonotocityNot monotonic
2021-02-18T22:38:25.177925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
028
26.2%
110
 
9.3%
46
 
5.6%
26
 
5.6%
34
 
3.7%
163
 
2.8%
73
 
2.8%
152
 
1.9%
102
 
1.9%
122
 
1.9%
Other values (36)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
110
 
9.3%
26
 
5.6%
34
 
3.7%
46
 
5.6%
ValueCountFrequency (%)
3081
0.9%
2751
0.9%
1991
0.9%
1781
0.9%
1711
0.9%

CGD CARCASSONNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean30.65048544
Minimum0
Maximum313
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:38:25.284936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q328.5
95-th percentile152.8
Maximum313
Range313
Interquartile range (IQR)28.5

Descriptive statistics

Standard deviation57.42389827
Coefficient of variation (CV)1.873506976
Kurtosis8.30166762
Mean30.65048544
Median Absolute Deviation (MAD)4
Skewness2.775825688
Sum3157
Variance3297.504093
MonotocityNot monotonic
2021-02-18T22:38:25.399946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
032
29.9%
18
 
7.5%
27
 
6.5%
63
 
2.8%
133
 
2.8%
43
 
2.8%
143
 
2.8%
32
 
1.9%
112
 
1.9%
312
 
1.9%
Other values (34)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
18
 
7.5%
27
 
6.5%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
3131
0.9%
2561
0.9%
2131
0.9%
1971
0.9%
1701
0.9%

CGD LIMOUX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct35
Distinct (%)34.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean14.13592233
Minimum0
Maximum144
Zeros41
Zeros (%)38.3%
Memory size984.0 B
2021-02-18T22:38:25.499855image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314.5
95-th percentile78.8
Maximum144
Range144
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation26.80066159
Coefficient of variation (CV)1.895925923
Kurtosis8.229999523
Mean14.13592233
Median Absolute Deviation (MAD)2
Skewness2.803416602
Sum1456
Variance718.2754616
MonotocityNot monotonic
2021-02-18T22:38:25.613118image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
041
38.3%
26
 
5.6%
16
 
5.6%
103
 
2.8%
43
 
2.8%
63
 
2.8%
93
 
2.8%
122
 
1.9%
282
 
1.9%
192
 
1.9%
Other values (25)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
041
38.3%
16
 
5.6%
26
 
5.6%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
1441
0.9%
1211
0.9%
921
0.9%
891
0.9%
861
0.9%

CGD NARBONNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean40.18446602
Minimum0
Maximum424
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:25.752918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q330.5
95-th percentile201.3
Maximum424
Range424
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation82.9363975
Coefficient of variation (CV)2.063891989
Kurtosis9.272267651
Mean40.18446602
Median Absolute Deviation (MAD)7
Skewness3.02637275
Sum4139
Variance6878.446031
MonotocityNot monotonic
2021-02-18T22:38:25.872121image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
024
22.4%
114
 
13.1%
26
 
5.6%
134
 
3.7%
183
 
2.8%
32
 
1.9%
92
 
1.9%
272
 
1.9%
82
 
1.9%
72
 
1.9%
Other values (37)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
114
13.1%
26
 
5.6%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
4241
0.9%
3871
0.9%
3411
0.9%
3131
0.9%
2991
0.9%

CGD MILLAU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct32
Distinct (%)31.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.13592233
Minimum0
Maximum183
Zeros39
Zeros (%)36.4%
Memory size984.0 B
2021-02-18T22:38:25.972240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q311
95-th percentile55.8
Maximum183
Range183
Interquartile range (IQR)11

Descriptive statistics

Standard deviation24.93522925
Coefficient of variation (CV)2.05466289
Kurtosis21.70225295
Mean12.13592233
Median Absolute Deviation (MAD)2
Skewness3.962333653
Sum1250
Variance621.7656577
MonotocityNot monotonic
2021-02-18T22:38:26.065910image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
039
36.4%
28
 
7.5%
18
 
7.5%
46
 
5.6%
35
 
4.7%
114
 
3.7%
63
 
2.8%
473
 
2.8%
172
 
1.9%
82
 
1.9%
Other values (22)23
21.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
039
36.4%
18
 
7.5%
28
 
7.5%
35
 
4.7%
46
 
5.6%
ValueCountFrequency (%)
1831
0.9%
861
0.9%
681
0.9%
651
0.9%
611
0.9%

CGD RODEZ
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.00970874
Minimum0
Maximum389
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:26.169822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q317
95-th percentile81.8
Maximum389
Range389
Interquartile range (IQR)17

Descriptive statistics

Standard deviation46.59472644
Coefficient of variation (CV)2.328605931
Kurtosis38.90750308
Mean20.00970874
Median Absolute Deviation (MAD)3
Skewness5.434946434
Sum2061
Variance2171.068532
MonotocityNot monotonic
2021-02-18T22:38:26.272921image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
035
32.7%
113
 
12.1%
84
 
3.7%
34
 
3.7%
103
 
2.8%
43
 
2.8%
163
 
2.8%
23
 
2.8%
92
 
1.9%
52
 
1.9%
Other values (28)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
113
 
12.1%
23
 
2.8%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
3891
0.9%
1381
0.9%
1281
0.9%
1101
0.9%
1001
0.9%

CGD VILLEFRANCHE DE ROUERGUE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct35
Distinct (%)34.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.38834951
Minimum0
Maximum202
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:26.380428image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q317.5
95-th percentile66
Maximum202
Range202
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation30.82691497
Coefficient of variation (CV)1.88102621
Kurtosis14.53997653
Mean16.38834951
Median Absolute Deviation (MAD)3
Skewness3.3497104
Sum1688
Variance950.2986865
MonotocityNot monotonic
2021-02-18T22:38:26.502434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
036
33.6%
111
 
10.3%
104
 
3.7%
64
 
3.7%
123
 
2.8%
53
 
2.8%
33
 
2.8%
23
 
2.8%
83
 
2.8%
152
 
1.9%
Other values (25)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
111
 
10.3%
23
 
2.8%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
2021
0.9%
1391
0.9%
1001
0.9%
901
0.9%
671
0.9%

CGD AIX EN PROVENCE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean57.84466019
Minimum0
Maximum620
Zeros22
Zeros (%)20.6%
Memory size984.0 B
2021-02-18T22:38:26.604273image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q337
95-th percentile345.6
Maximum620
Range620
Interquartile range (IQR)36

Descriptive statistics

Standard deviation121.0524726
Coefficient of variation (CV)2.092716462
Kurtosis9.362185092
Mean57.84466019
Median Absolute Deviation (MAD)7
Skewness3.003136712
Sum5958
Variance14653.70112
MonotocityNot monotonic
2021-02-18T22:38:26.712037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
022
20.6%
114
 
13.1%
26
 
5.6%
64
 
3.7%
93
 
2.8%
203
 
2.8%
232
 
1.9%
82
 
1.9%
852
 
1.9%
252
 
1.9%
Other values (39)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
022
20.6%
114
13.1%
26
 
5.6%
31
 
0.9%
42
 
1.9%
ValueCountFrequency (%)
6201
0.9%
6041
0.9%
4471
0.9%
4311
0.9%
3961
0.9%

CGD ARLES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean51.38834951
Minimum0
Maximum576
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:26.858720image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q349
95-th percentile328.9
Maximum576
Range576
Interquartile range (IQR)48

Descriptive statistics

Standard deviation106.0051084
Coefficient of variation (CV)2.06282376
Kurtosis9.502838499
Mean51.38834951
Median Absolute Deviation (MAD)9
Skewness3.039476824
Sum5293
Variance11237.083
MonotocityNot monotonic
2021-02-18T22:38:26.980906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
024
22.4%
110
 
9.3%
26
 
5.6%
43
 
2.8%
73
 
2.8%
33
 
2.8%
192
 
1.9%
172
 
1.9%
202
 
1.9%
112
 
1.9%
Other values (40)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
110
9.3%
26
 
5.6%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
5761
0.9%
4851
0.9%
3921
0.9%
3511
0.9%
3421
0.9%

CGD AUBAGNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean34.33009709
Minimum0
Maximum403
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:27.086349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q321
95-th percentile202.5
Maximum403
Range403
Interquartile range (IQR)21

Descriptive statistics

Standard deviation72.6981927
Coefficient of variation (CV)2.117622695
Kurtosis10.00097051
Mean34.33009709
Median Absolute Deviation (MAD)4
Skewness3.060039307
Sum3536
Variance5285.027223
MonotocityNot monotonic
2021-02-18T22:38:27.182832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
028
26.2%
114
 
13.1%
25
 
4.7%
34
 
3.7%
53
 
2.8%
63
 
2.8%
172
 
1.9%
152
 
1.9%
532
 
1.9%
232
 
1.9%
Other values (32)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
114
13.1%
25
 
4.7%
34
 
3.7%
41
 
0.9%
ValueCountFrequency (%)
4031
0.9%
3341
0.9%
2811
0.9%
2511
0.9%
2151
0.9%

CGD ISTRES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.74757282
Minimum0
Maximum344
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:38:27.283353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q324
95-th percentile161.3
Maximum344
Range344
Interquartile range (IQR)24

Descriptive statistics

Standard deviation57.52454181
Coefficient of variation (CV)2.073137791
Kurtosis11.0998668
Mean27.74757282
Median Absolute Deviation (MAD)3
Skewness3.140300642
Sum2858
Variance3309.072911
MonotocityNot monotonic
2021-02-18T22:38:27.377420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
031
29.0%
111
 
10.3%
28
 
7.5%
63
 
2.8%
33
 
2.8%
132
 
1.9%
72
 
1.9%
192
 
1.9%
402
 
1.9%
52
 
1.9%
Other values (33)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
111
 
10.3%
28
 
7.5%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
3441
0.9%
2411
0.9%
1991
0.9%
1881
0.9%
1791
0.9%

CGD SALON DE PROVENCE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean55.3592233
Minimum0
Maximum609
Zeros20
Zeros (%)18.7%
Memory size984.0 B
2021-02-18T22:38:27.480133image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q344
95-th percentile320.8
Maximum609
Range609
Interquartile range (IQR)43

Descriptive statistics

Standard deviation114.7502706
Coefficient of variation (CV)2.072830212
Kurtosis10.7435384
Mean55.3592233
Median Absolute Deviation (MAD)8
Skewness3.165629789
Sum5702
Variance13167.6246
MonotocityNot monotonic
2021-02-18T22:38:27.576880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
020
18.7%
211
 
10.3%
19
 
8.4%
35
 
4.7%
43
 
2.8%
613
 
2.8%
132
 
1.9%
242
 
1.9%
142
 
1.9%
232
 
1.9%
Other values (39)44
41.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
020
18.7%
19
8.4%
211
10.3%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
6091
0.9%
5921
0.9%
4731
0.9%
3461
0.9%
3411
0.9%

CGD BAYEUX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean21.51456311
Minimum0
Maximum260
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:27.672963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q321.5
95-th percentile105.1
Maximum260
Range260
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation42.13048453
Coefficient of variation (CV)1.958231005
Kurtosis12.37054281
Mean21.51456311
Median Absolute Deviation (MAD)4
Skewness3.24586632
Sum2216
Variance1774.977727
MonotocityNot monotonic
2021-02-18T22:38:27.769418image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
034
31.8%
36
 
5.6%
16
 
5.6%
25
 
4.7%
134
 
3.7%
53
 
2.8%
43
 
2.8%
213
 
2.8%
102
 
1.9%
62
 
1.9%
Other values (30)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
16
 
5.6%
25
 
4.7%
36
 
5.6%
43
 
2.8%
ValueCountFrequency (%)
2601
0.9%
1781
0.9%
1581
0.9%
1521
0.9%
1171
0.9%

CGD CAEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.25242718
Minimum0
Maximum322
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:27.887299image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q325
95-th percentile158.2
Maximum322
Range322
Interquartile range (IQR)25

Descriptive statistics

Standard deviation54.04531839
Coefficient of variation (CV)1.912944259
Kurtosis10.58835308
Mean28.25242718
Median Absolute Deviation (MAD)5
Skewness3.049473816
Sum2910
Variance2920.89644
MonotocityNot monotonic
2021-02-18T22:38:28.019110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
033
30.8%
46
 
5.6%
34
 
3.7%
24
 
3.7%
113
 
2.8%
63
 
2.8%
13
 
2.8%
192
 
1.9%
222
 
1.9%
242
 
1.9%
Other values (38)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
13
 
2.8%
24
 
3.7%
34
 
3.7%
46
 
5.6%
ValueCountFrequency (%)
3221
0.9%
2111
0.9%
2011
0.9%
1931
0.9%
1761
0.9%

CGD DEAUVILLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct31
Distinct (%)30.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean11.7961165
Minimum0
Maximum156
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:28.132181image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310
95-th percentile59.9
Maximum156
Range156
Interquartile range (IQR)10

Descriptive statistics

Standard deviation23.93879419
Coefficient of variation (CV)2.02937926
Kurtosis14.52193406
Mean11.7961165
Median Absolute Deviation (MAD)2
Skewness3.464688968
Sum1215
Variance573.0658671
MonotocityNot monotonic
2021-02-18T22:38:28.217712image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
034
31.8%
110
 
9.3%
29
 
8.4%
75
 
4.7%
65
 
4.7%
54
 
3.7%
43
 
2.8%
133
 
2.8%
103
 
2.8%
32
 
1.9%
Other values (21)25
23.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
110
 
9.3%
29
 
8.4%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
1561
0.9%
911
0.9%
871
0.9%
801
0.9%
751
0.9%

CGD FALAISE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.40776699
Minimum0
Maximum236
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:38:28.310481image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q317
95-th percentile89.8
Maximum236
Range236
Interquartile range (IQR)17

Descriptive statistics

Standard deviation37.56443794
Coefficient of variation (CV)1.935536322
Kurtosis13.2119618
Mean19.40776699
Median Absolute Deviation (MAD)4
Skewness3.289687456
Sum1999
Variance1411.086998
MonotocityNot monotonic
2021-02-18T22:38:28.741940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
032
29.9%
111
 
10.3%
25
 
4.7%
45
 
4.7%
33
 
2.8%
63
 
2.8%
93
 
2.8%
173
 
2.8%
332
 
1.9%
132
 
1.9%
Other values (29)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
111
 
10.3%
25
 
4.7%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
2361
0.9%
1751
0.9%
1301
0.9%
1081
0.9%
931
0.9%

CGD LISIEUX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct33
Distinct (%)32.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean11.24271845
Minimum0
Maximum127
Zeros42
Zeros (%)39.3%
Memory size984.0 B
2021-02-18T22:38:28.834221image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q312
95-th percentile58
Maximum127
Range127
Interquartile range (IQR)12

Descriptive statistics

Standard deviation21.58179426
Coefficient of variation (CV)1.919624187
Kurtosis11.78415726
Mean11.24271845
Median Absolute Deviation (MAD)2
Skewness3.164414583
Sum1158
Variance465.7738435
MonotocityNot monotonic
2021-02-18T22:38:28.925349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
042
39.3%
29
 
8.4%
18
 
7.5%
66
 
5.6%
123
 
2.8%
42
 
1.9%
102
 
1.9%
142
 
1.9%
92
 
1.9%
252
 
1.9%
Other values (23)25
23.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
042
39.3%
18
 
7.5%
29
 
8.4%
42
 
1.9%
51
 
0.9%
ValueCountFrequency (%)
1271
0.9%
1091
0.9%
731
0.9%
641
0.9%
621
0.9%

CGD VIRE NORMANDIE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean14.61165049
Minimum0
Maximum196
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:38:29.016945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q316
95-th percentile61.5
Maximum196
Range196
Interquartile range (IQR)16

Descriptive statistics

Standard deviation28.90662215
Coefficient of variation (CV)1.978326964
Kurtosis19.55349105
Mean14.61165049
Median Absolute Deviation (MAD)3
Skewness3.955081245
Sum1505
Variance835.5928041
MonotocityNot monotonic
2021-02-18T22:38:29.108288image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
038
35.5%
16
 
5.6%
25
 
4.7%
54
 
3.7%
44
 
3.7%
34
 
3.7%
133
 
2.8%
263
 
2.8%
143
 
2.8%
322
 
1.9%
Other values (26)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
16
 
5.6%
25
 
4.7%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
1961
0.9%
1541
0.9%
871
0.9%
751
0.9%
622
1.9%

CGD AURILLAC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct30
Distinct (%)29.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean10.54368932
Minimum0
Maximum125
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:38:29.198553image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q311
95-th percentile45
Maximum125
Range125
Interquartile range (IQR)11

Descriptive statistics

Standard deviation20.93349727
Coefficient of variation (CV)1.985405358
Kurtosis13.49413368
Mean10.54368932
Median Absolute Deviation (MAD)2
Skewness3.41205081
Sum1086
Variance438.2113078
MonotocityNot monotonic
2021-02-18T22:38:29.287223image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
038
35.5%
18
 
7.5%
26
 
5.6%
46
 
5.6%
36
 
5.6%
75
 
4.7%
53
 
2.8%
113
 
2.8%
322
 
1.9%
452
 
1.9%
Other values (20)24
22.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
18
 
7.5%
26
 
5.6%
36
 
5.6%
46
 
5.6%
ValueCountFrequency (%)
1251
0.9%
1091
0.9%
811
0.9%
591
0.9%
581
0.9%

CGD MAURIAC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct28
Distinct (%)27.2%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean6.067961165
Minimum0
Maximum84
Zeros46
Zeros (%)43.0%
Memory size984.0 B
2021-02-18T22:38:29.374963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile27.9
Maximum84
Range84
Interquartile range (IQR)6

Descriptive statistics

Standard deviation12.24365553
Coefficient of variation (CV)2.017754431
Kurtosis17.18593448
Mean6.067961165
Median Absolute Deviation (MAD)1
Skewness3.620608586
Sum625
Variance149.9071007
MonotocityNot monotonic
2021-02-18T22:38:29.455341image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
046
43.0%
114
 
13.1%
26
 
5.6%
44
 
3.7%
53
 
2.8%
63
 
2.8%
282
 
1.9%
112
 
1.9%
32
 
1.9%
102
 
1.9%
Other values (18)19
17.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
046
43.0%
114
 
13.1%
26
 
5.6%
32
 
1.9%
44
 
3.7%
ValueCountFrequency (%)
841
0.9%
501
0.9%
401
0.9%
361
0.9%
282
1.9%

CGD ST FLOUR
Real number (ℝ≥0)

MISSING
ZEROS

Distinct24
Distinct (%)23.3%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean8.611650485
Minimum0
Maximum139
Zeros42
Zeros (%)39.3%
Memory size984.0 B
2021-02-18T22:38:29.552587image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile37.8
Maximum139
Range139
Interquartile range (IQR)6

Descriptive statistics

Standard deviation19.73413138
Coefficient of variation (CV)2.291562043
Kurtosis21.23154052
Mean8.611650485
Median Absolute Deviation (MAD)1
Skewness4.183962199
Sum887
Variance389.4359414
MonotocityNot monotonic
2021-02-18T22:38:29.664271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
042
39.3%
110
 
9.3%
38
 
7.5%
67
 
6.5%
45
 
4.7%
54
 
3.7%
24
 
3.7%
123
 
2.8%
232
 
1.9%
152
 
1.9%
Other values (14)16
 
15.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
042
39.3%
110
 
9.3%
24
 
3.7%
38
 
7.5%
45
 
4.7%
ValueCountFrequency (%)
1391
0.9%
831
0.9%
731
0.9%
701
0.9%
431
0.9%

CGD ANGOULEME
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.99029126
Minimum0
Maximum416
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:29.783251image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q325
95-th percentile112.5
Maximum416
Range416
Interquartile range (IQR)25

Descriptive statistics

Standard deviation53.81240019
Coefficient of variation (CV)2.243090741
Kurtosis28.22653498
Mean23.99029126
Median Absolute Deviation (MAD)2
Skewness4.626575481
Sum2471
Variance2895.774415
MonotocityNot monotonic
2021-02-18T22:38:29.877274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
034
31.8%
112
 
11.2%
27
 
6.5%
105
 
4.7%
113
 
2.8%
153
 
2.8%
422
 
1.9%
302
 
1.9%
312
 
1.9%
42
 
1.9%
Other values (30)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
112
 
11.2%
27
 
6.5%
42
 
1.9%
51
 
0.9%
ValueCountFrequency (%)
4161
0.9%
1741
0.9%
1731
0.9%
1491
0.9%
1451
0.9%

CGD COGNAC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.59223301
Minimum0
Maximum293
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:38:29.969029image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q318
95-th percentile99.9
Maximum293
Range293
Interquartile range (IQR)18

Descriptive statistics

Standard deviation40.24153471
Coefficient of variation (CV)2.053953456
Kurtosis21.36342949
Mean19.59223301
Median Absolute Deviation (MAD)2
Skewness3.986696336
Sum2018
Variance1619.381116
MonotocityNot monotonic
2021-02-18T22:38:30.062811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
038
35.5%
18
 
7.5%
26
 
5.6%
84
 
3.7%
182
 
1.9%
142
 
1.9%
62
 
1.9%
112
 
1.9%
52
 
1.9%
92
 
1.9%
Other values (32)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
18
 
7.5%
26
 
5.6%
31
 
0.9%
41
 
0.9%
ValueCountFrequency (%)
2931
0.9%
1361
0.9%
1351
0.9%
1081
0.9%
1031
0.9%

CGD CONFOLENS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.15533981
Minimum0
Maximum339
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:30.196900image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q326
95-th percentile106.3
Maximum339
Range339
Interquartile range (IQR)26

Descriptive statistics

Standard deviation48.27124287
Coefficient of variation (CV)2.084670027
Kurtosis20.27878354
Mean23.15533981
Median Absolute Deviation (MAD)3
Skewness3.994740403
Sum2385
Variance2330.112888
MonotocityNot monotonic
2021-02-18T22:38:30.318007image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
035
32.7%
28
 
7.5%
18
 
7.5%
123
 
2.8%
53
 
2.8%
142
 
1.9%
542
 
1.9%
172
 
1.9%
402
 
1.9%
152
 
1.9%
Other values (31)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
18
 
7.5%
28
 
7.5%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
3391
0.9%
2231
0.9%
1611
0.9%
1161
0.9%
1151
0.9%

CGD JONZAC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.63106796
Minimum0
Maximum214
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:30.426309image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q322
95-th percentile122.9
Maximum214
Range214
Interquartile range (IQR)22

Descriptive statistics

Standard deviation43.21287714
Coefficient of variation (CV)1.828646814
Kurtosis6.151280321
Mean23.63106796
Median Absolute Deviation (MAD)3
Skewness2.490566172
Sum2434
Variance1867.352751
MonotocityNot monotonic
2021-02-18T22:38:30.516795image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
027
25.2%
115
14.0%
28
 
7.5%
34
 
3.7%
44
 
3.7%
133
 
2.8%
162
 
1.9%
112
 
1.9%
212
 
1.9%
232
 
1.9%
Other values (32)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
115
14.0%
28
 
7.5%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
2141
0.9%
1841
0.9%
1711
0.9%
1461
0.9%
1311
0.9%

CGD LA ROCHELLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean41.06796117
Minimum0
Maximum508
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:38:30.610727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median5
Q333.5
95-th percentile237
Maximum508
Range508
Interquartile range (IQR)33

Descriptive statistics

Standard deviation85.34661303
Coefficient of variation (CV)2.078179939
Kurtosis12.3888357
Mean41.06796117
Median Absolute Deviation (MAD)5
Skewness3.302207728
Sum4230
Variance7284.044356
MonotocityNot monotonic
2021-02-18T22:38:30.713599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
026
24.3%
114
 
13.1%
45
 
4.7%
24
 
3.7%
183
 
2.8%
193
 
2.8%
53
 
2.8%
83
 
2.8%
422
 
1.9%
72
 
1.9%
Other values (37)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
114
13.1%
24
 
3.7%
31
 
0.9%
45
 
4.7%
ValueCountFrequency (%)
5081
0.9%
4101
0.9%
3251
0.9%
2511
0.9%
2421
0.9%

CGD ROCHEFORT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct53
Distinct (%)51.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean47.47572816
Minimum0
Maximum432
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:38:30.817637image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q339.5
95-th percentile232.2
Maximum432
Range432
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation89.528377
Coefficient of variation (CV)1.88577154
Kurtosis7.218362665
Mean47.47572816
Median Absolute Deviation (MAD)8
Skewness2.6702601
Sum4890
Variance8015.330287
MonotocityNot monotonic
2021-02-18T22:38:30.915429image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
025
23.4%
19
 
8.4%
46
 
5.6%
25
 
4.7%
253
 
2.8%
33
 
2.8%
282
 
1.9%
232
 
1.9%
472
 
1.9%
82
 
1.9%
Other values (43)44
41.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
19
 
8.4%
25
 
4.7%
33
 
2.8%
46
 
5.6%
ValueCountFrequency (%)
4321
0.9%
4241
0.9%
3671
0.9%
3131
0.9%
2611
0.9%

CGD SAINTES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.03883495
Minimum0
Maximum318
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:38:31.010782image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q320
95-th percentile118.1
Maximum318
Range318
Interquartile range (IQR)20

Descriptive statistics

Standard deviation52.37008619
Coefficient of variation (CV)2.091554431
Kurtosis13.33500966
Mean25.03883495
Median Absolute Deviation (MAD)3
Skewness3.412202498
Sum2579
Variance2742.625928
MonotocityNot monotonic
2021-02-18T22:38:31.102558image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
031
29.0%
113
 
12.1%
34
 
3.7%
24
 
3.7%
63
 
2.8%
93
 
2.8%
173
 
2.8%
43
 
2.8%
203
 
2.8%
112
 
1.9%
Other values (30)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
113
12.1%
24
 
3.7%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
3181
0.9%
2371
0.9%
2291
0.9%
1701
0.9%
1291
0.9%

CGD ST JEAN D ANGELY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.53398058
Minimum0
Maximum147
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:31.199241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q316.5
95-th percentile90.2
Maximum147
Range147
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation30.65680219
Coefficient of variation (CV)1.748422273
Kurtosis5.351144289
Mean17.53398058
Median Absolute Deviation (MAD)5
Skewness2.366864825
Sum1806
Variance939.8395203
MonotocityNot monotonic
2021-02-18T22:38:31.289553image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
034
31.8%
112
 
11.2%
76
 
5.6%
55
 
4.7%
63
 
2.8%
43
 
2.8%
123
 
2.8%
142
 
1.9%
82
 
1.9%
112
 
1.9%
Other values (30)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
112
 
11.2%
31
 
0.9%
43
 
2.8%
55
 
4.7%
ValueCountFrequency (%)
1471
0.9%
1311
0.9%
1151
0.9%
1041
0.9%
941
0.9%

CGD BOURGES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.24271845
Minimum0
Maximum203
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:31.386317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q317.5
95-th percentile77
Maximum203
Range203
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation31.7445274
Coefficient of variation (CV)1.95438513
Kurtosis13.28125035
Mean16.24271845
Median Absolute Deviation (MAD)2
Skewness3.27640949
Sum1673
Variance1007.71502
MonotocityNot monotonic
2021-02-18T22:38:31.480760image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
035
32.7%
112
 
11.2%
28
 
7.5%
184
 
3.7%
84
 
3.7%
63
 
2.8%
33
 
2.8%
172
 
1.9%
42
 
1.9%
552
 
1.9%
Other values (27)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
112
 
11.2%
28
 
7.5%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
2031
0.9%
1221
0.9%
1171
0.9%
1131
0.9%
921
0.9%

CGD ST AMAND MONTROND
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.57281553
Minimum0
Maximum215
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:31.583523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q321.5
95-th percentile96.2
Maximum215
Range215
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation38.98984331
Coefficient of variation (CV)1.895211827
Kurtosis9.537157131
Mean20.57281553
Median Absolute Deviation (MAD)2
Skewness2.875503768
Sum2119
Variance1520.207881
MonotocityNot monotonic
2021-02-18T22:38:31.676610image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
037
34.6%
114
 
13.1%
25
 
4.7%
502
 
1.9%
252
 
1.9%
52
 
1.9%
102
 
1.9%
132
 
1.9%
42
 
1.9%
62
 
1.9%
Other values (33)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
114
 
13.1%
25
 
4.7%
31
 
0.9%
42
 
1.9%
ValueCountFrequency (%)
2151
0.9%
1921
0.9%
1531
0.9%
1071
0.9%
981
0.9%

CGD VIERZON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean15.02912621
Minimum0
Maximum200
Zeros39
Zeros (%)36.4%
Memory size984.0 B
2021-02-18T22:38:31.769664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q313.5
95-th percentile78.3
Maximum200
Range200
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation30.8311201
Coefficient of variation (CV)2.051424658
Kurtosis14.24574849
Mean15.02912621
Median Absolute Deviation (MAD)1
Skewness3.386443816
Sum1548
Variance950.5579669
MonotocityNot monotonic
2021-02-18T22:38:31.862164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
039
36.4%
113
 
12.1%
25
 
4.7%
83
 
2.8%
93
 
2.8%
33
 
2.8%
72
 
1.9%
42
 
1.9%
52
 
1.9%
622
 
1.9%
Other values (24)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
039
36.4%
113
 
12.1%
25
 
4.7%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
2001
0.9%
1291
0.9%
1061
0.9%
882
1.9%
801
0.9%

CGD BRIVE LA GAILLARDE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.2815534
Minimum0
Maximum412
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:31.963922image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q326.5
95-th percentile121.5
Maximum412
Range412
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation53.52815229
Coefficient of variation (CV)2.117280985
Kurtosis27.11404616
Mean25.2815534
Median Absolute Deviation (MAD)5
Skewness4.479145778
Sum2604
Variance2865.263088
MonotocityNot monotonic
2021-02-18T22:38:32.057137image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
036
33.6%
16
 
5.6%
34
 
3.7%
54
 
3.7%
123
 
2.8%
23
 
2.8%
93
 
2.8%
142
 
1.9%
42
 
1.9%
482
 
1.9%
Other values (33)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
16
 
5.6%
23
 
2.8%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
4121
0.9%
1921
0.9%
1401
0.9%
1331
0.9%
1291
0.9%

CGD USSEL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12
Minimum0
Maximum216
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:32.150410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310
95-th percentile51.5
Maximum216
Range216
Interquartile range (IQR)10

Descriptive statistics

Standard deviation27.04136265
Coefficient of variation (CV)2.253446888
Kurtosis32.80633438
Mean12
Median Absolute Deviation (MAD)2
Skewness5.024631525
Sum1236
Variance731.2352941
MonotocityNot monotonic
2021-02-18T22:38:32.236683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
037
34.6%
112
 
11.2%
25
 
4.7%
75
 
4.7%
34
 
3.7%
94
 
3.7%
103
 
2.8%
43
 
2.8%
82
 
1.9%
122
 
1.9%
Other values (24)26
24.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
112
 
11.2%
25
 
4.7%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
2161
0.9%
1051
0.9%
771
0.9%
701
0.9%
531
0.9%

CGD BEAUNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.49514563
Minimum0
Maximum224
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:38:32.330649image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q316.5
95-th percentile95.9
Maximum224
Range224
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation37.83604304
Coefficient of variation (CV)1.940793044
Kurtosis11.19566192
Mean19.49514563
Median Absolute Deviation (MAD)4
Skewness3.101691068
Sum2008
Variance1431.566153
MonotocityNot monotonic
2021-02-18T22:38:32.446802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
032
29.9%
29
 
8.4%
16
 
5.6%
65
 
4.7%
44
 
3.7%
34
 
3.7%
133
 
2.8%
93
 
2.8%
103
 
2.8%
952
 
1.9%
Other values (28)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
16
 
5.6%
29
 
8.4%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
2241
0.9%
1821
0.9%
1261
0.9%
1091
0.9%
1001
0.9%

CGD DIJON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean34.6407767
Minimum0
Maximum434
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:38:32.569830image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q324
95-th percentile148
Maximum434
Range434
Interquartile range (IQR)24

Descriptive statistics

Standard deviation70.03680466
Coefficient of variation (CV)2.021802377
Kurtosis11.96408364
Mean34.6407767
Median Absolute Deviation (MAD)7
Skewness3.165038398
Sum3568
Variance4905.154007
MonotocityNot monotonic
2021-02-18T22:38:33.171616image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
031
29.0%
19
 
8.4%
75
 
4.7%
54
 
3.7%
154
 
3.7%
93
 
2.8%
23
 
2.8%
232
 
1.9%
1482
 
1.9%
112
 
1.9%
Other values (31)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
19
 
8.4%
23
 
2.8%
42
 
1.9%
54
 
3.7%
ValueCountFrequency (%)
4341
0.9%
2671
0.9%
2531
0.9%
2382
1.9%
1482
1.9%

CGD IS SUR TILLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct32
Distinct (%)31.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean13.49514563
Minimum0
Maximum210
Zeros41
Zeros (%)38.3%
Memory size984.0 B
2021-02-18T22:38:33.266109image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q310
95-th percentile69.6
Maximum210
Range210
Interquartile range (IQR)10

Descriptive statistics

Standard deviation29.81343091
Coefficient of variation (CV)2.209196679
Kurtosis19.99228176
Mean13.49514563
Median Absolute Deviation (MAD)1
Skewness3.971682626
Sum1390
Variance888.8406625
MonotocityNot monotonic
2021-02-18T22:38:33.350584image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
041
38.3%
111
 
10.3%
45
 
4.7%
85
 
4.7%
65
 
4.7%
23
 
2.8%
103
 
2.8%
53
 
2.8%
252
 
1.9%
32
 
1.9%
Other values (22)23
21.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
041
38.3%
111
 
10.3%
23
 
2.8%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
2101
0.9%
1142
1.9%
771
0.9%
751
0.9%
701
0.9%

CGD MONTBARD
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.16504854
Minimum0
Maximum211
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:38:33.441434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q317.5
95-th percentile95.8
Maximum211
Range211
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation38.53902964
Coefficient of variation (CV)2.010901749
Kurtosis11.30455021
Mean19.16504854
Median Absolute Deviation (MAD)3
Skewness3.22862411
Sum1974
Variance1485.256806
MonotocityNot monotonic
2021-02-18T22:38:33.530931image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
038
35.5%
36
 
5.6%
74
 
3.7%
14
 
3.7%
24
 
3.7%
83
 
2.8%
113
 
2.8%
52
 
1.9%
272
 
1.9%
942
 
1.9%
Other values (31)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
14
 
3.7%
24
 
3.7%
36
 
5.6%
41
 
0.9%
ValueCountFrequency (%)
2111
0.9%
1991
0.9%
1561
0.9%
1281
0.9%
1021
0.9%

CGD DINAN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean35.40776699
Minimum0
Maximum494
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:33.622374image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q324
95-th percentile208.9
Maximum494
Range494
Interquartile range (IQR)24

Descriptive statistics

Standard deviation74.43689746
Coefficient of variation (CV)2.102275963
Kurtosis15.83451252
Mean35.40776699
Median Absolute Deviation (MAD)5
Skewness3.576221721
Sum3647
Variance5540.851704
MonotocityNot monotonic
2021-02-18T22:38:33.722771image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
033
30.8%
27
 
6.5%
15
 
4.7%
75
 
4.7%
204
 
3.7%
34
 
3.7%
53
 
2.8%
182
 
1.9%
852
 
1.9%
212
 
1.9%
Other values (34)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
15
 
4.7%
27
 
6.5%
34
 
3.7%
41
 
0.9%
ValueCountFrequency (%)
4941
0.9%
3151
0.9%
2361
0.9%
2201
0.9%
2171
0.9%

CGD GUINGAMP
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.7184466
Minimum0
Maximum329
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:38:33.819926image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q326
95-th percentile130.8
Maximum329
Range329
Interquartile range (IQR)26

Descriptive statistics

Standard deviation52.04832172
Coefficient of variation (CV)2.023773929
Kurtosis14.04506166
Mean25.7184466
Median Absolute Deviation (MAD)4
Skewness3.411009232
Sum2649
Variance2709.027794
MonotocityNot monotonic
2021-02-18T22:38:33.913135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
030
28.0%
112
 
11.2%
47
 
6.5%
24
 
3.7%
124
 
3.7%
283
 
2.8%
113
 
2.8%
33
 
2.8%
82
 
1.9%
132
 
1.9%
Other values (32)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
112
 
11.2%
24
 
3.7%
33
 
2.8%
47
 
6.5%
ValueCountFrequency (%)
3291
0.9%
2491
0.9%
1621
0.9%
1521
0.9%
1441
0.9%

CGD LANNION
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean24.84466019
Minimum0
Maximum348
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:34.011487image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q325
95-th percentile103.5
Maximum348
Range348
Interquartile range (IQR)25

Descriptive statistics

Standard deviation51.25422169
Coefficient of variation (CV)2.06298743
Kurtosis18.63251942
Mean24.84466019
Median Absolute Deviation (MAD)3
Skewness3.881092621
Sum2559
Variance2626.995241
MonotocityNot monotonic
2021-02-18T22:38:34.107595image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
027
25.2%
114
 
13.1%
28
 
7.5%
34
 
3.7%
43
 
2.8%
152
 
1.9%
132
 
1.9%
122
 
1.9%
252
 
1.9%
922
 
1.9%
Other values (33)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
114
13.1%
28
 
7.5%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
3481
0.9%
2491
0.9%
1821
0.9%
1341
0.9%
1201
0.9%

CGD ST BRIEUC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct51
Distinct (%)49.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean52.26213592
Minimum0
Maximum641
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:38:34.235803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q343
95-th percentile266.3
Maximum641
Range641
Interquartile range (IQR)42

Descriptive statistics

Standard deviation102.6477855
Coefficient of variation (CV)1.964094725
Kurtosis12.93208672
Mean52.26213592
Median Absolute Deviation (MAD)9
Skewness3.285662283
Sum5383
Variance10536.56787
MonotocityNot monotonic
2021-02-18T22:38:34.357384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
025
23.4%
18
 
7.5%
26
 
5.6%
93
 
2.8%
83
 
2.8%
333
 
2.8%
33
 
2.8%
242
 
1.9%
432
 
1.9%
262
 
1.9%
Other values (41)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
18
 
7.5%
26
 
5.6%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
6411
0.9%
4651
0.9%
3641
0.9%
3131
0.9%
2751
0.9%

CGD AUBUSSON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct28
Distinct (%)27.2%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean10.22330097
Minimum0
Maximum150
Zeros39
Zeros (%)36.4%
Memory size984.0 B
2021-02-18T22:38:34.456419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310
95-th percentile47
Maximum150
Range150
Interquartile range (IQR)10

Descriptive statistics

Standard deviation21.00976992
Coefficient of variation (CV)2.055086706
Kurtosis20.43949041
Mean10.22330097
Median Absolute Deviation (MAD)2
Skewness3.993554452
Sum1053
Variance441.4104321
MonotocityNot monotonic
2021-02-18T22:38:34.540150image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
039
36.4%
110
 
9.3%
106
 
5.6%
96
 
5.6%
25
 
4.7%
64
 
3.7%
73
 
2.8%
53
 
2.8%
43
 
2.8%
242
 
1.9%
Other values (18)22
20.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
039
36.4%
110
 
9.3%
25
 
4.7%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
1501
0.9%
752
1.9%
681
0.9%
641
0.9%
481
0.9%

CGD GUERET
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.08737864
Minimum0
Maximum196
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:34.635128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q318.5
95-th percentile76.3
Maximum196
Range196
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation32.52573846
Coefficient of variation (CV)1.903494922
Kurtosis11.75818892
Mean17.08737864
Median Absolute Deviation (MAD)3
Skewness3.177737596
Sum1760
Variance1057.923663
MonotocityNot monotonic
2021-02-18T22:38:34.729463image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
034
31.8%
112
 
11.2%
25
 
4.7%
115
 
4.7%
45
 
4.7%
133
 
2.8%
53
 
2.8%
512
 
1.9%
222
 
1.9%
102
 
1.9%
Other values (26)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
112
 
11.2%
25
 
4.7%
31
 
0.9%
45
 
4.7%
ValueCountFrequency (%)
1961
0.9%
1461
0.9%
1231
0.9%
1121
0.9%
1041
0.9%

CGD BERGERAC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.7961165
Minimum0
Maximum233
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:34.825628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q313.5
95-th percentile77.5
Maximum233
Range233
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation34.73269331
Coefficient of variation (CV)2.067900238
Kurtosis16.81688638
Mean16.7961165
Median Absolute Deviation (MAD)3
Skewness3.699164311
Sum1730
Variance1206.359985
MonotocityNot monotonic
2021-02-18T22:38:34.916520image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
036
33.6%
28
 
7.5%
17
 
6.5%
126
 
5.6%
74
 
3.7%
33
 
2.8%
83
 
2.8%
103
 
2.8%
152
 
1.9%
442
 
1.9%
Other values (27)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
17
 
6.5%
28
 
7.5%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
2331
0.9%
1451
0.9%
1261
0.9%
1241
0.9%
811
0.9%

CGD NONTRON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.27184466
Minimum0
Maximum258
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:38:35.005544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q318.5
95-th percentile82
Maximum258
Range258
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation38.9932609
Coefficient of variation (CV)2.023327896
Kurtosis16.10313435
Mean19.27184466
Median Absolute Deviation (MAD)2
Skewness3.597102507
Sum1985
Variance1520.474396
MonotocityNot monotonic
2021-02-18T22:38:35.101427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
038
35.5%
18
 
7.5%
26
 
5.6%
85
 
4.7%
43
 
2.8%
243
 
2.8%
112
 
1.9%
92
 
1.9%
142
 
1.9%
822
 
1.9%
Other values (27)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
18
 
7.5%
26
 
5.6%
43
 
2.8%
52
 
1.9%
ValueCountFrequency (%)
2581
0.9%
1751
0.9%
1481
0.9%
1031
0.9%
1001
0.9%

CGD PERIGUEUX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.27184466
Minimum0
Maximum299
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:35.196780image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q321
95-th percentile107.6
Maximum299
Range299
Interquartile range (IQR)21

Descriptive statistics

Standard deviation45.73585588
Coefficient of variation (CV)1.96528709
Kurtosis15.03393237
Mean23.27184466
Median Absolute Deviation (MAD)4
Skewness3.497099867
Sum2397
Variance2091.768513
MonotocityNot monotonic
2021-02-18T22:38:35.313435image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
034
31.8%
18
 
7.5%
26
 
5.6%
214
 
3.7%
123
 
2.8%
33
 
2.8%
153
 
2.8%
142
 
1.9%
412
 
1.9%
192
 
1.9%
Other values (30)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
18
 
7.5%
26
 
5.6%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
2991
0.9%
1871
0.9%
1761
0.9%
1641
0.9%
1131
0.9%

CGD SARLAT LA CANEDA
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.12621359
Minimum0
Maximum344
Zeros41
Zeros (%)38.3%
Memory size984.0 B
2021-02-18T22:38:35.447078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q315
95-th percentile83.7
Maximum344
Range344
Interquartile range (IQR)15

Descriptive statistics

Standard deviation44.82223704
Coefficient of variation (CV)2.343497673
Kurtosis28.38653691
Mean19.12621359
Median Absolute Deviation (MAD)3
Skewness4.722058778
Sum1970
Variance2009.032934
MonotocityNot monotonic
2021-02-18T22:38:35.564245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
041
38.3%
15
 
4.7%
25
 
4.7%
74
 
3.7%
133
 
2.8%
63
 
2.8%
113
 
2.8%
93
 
2.8%
153
 
2.8%
32
 
1.9%
Other values (27)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
041
38.3%
15
 
4.7%
25
 
4.7%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
3441
0.9%
1681
0.9%
1511
0.9%
1281
0.9%
1191
0.9%

CGD BESANCON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean32.95145631
Minimum0
Maximum402
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:35.672804image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q330
95-th percentile140.5
Maximum402
Range402
Interquartile range (IQR)29

Descriptive statistics

Standard deviation61.6480171
Coefficient of variation (CV)1.870873825
Kurtosis13.44564382
Mean32.95145631
Median Absolute Deviation (MAD)5
Skewness3.229001771
Sum3394
Variance3800.478013
MonotocityNot monotonic
2021-02-18T22:38:35.776418image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
024
22.4%
29
 
8.4%
18
 
7.5%
47
 
6.5%
152
 
1.9%
82
 
1.9%
262
 
1.9%
552
 
1.9%
142
 
1.9%
182
 
1.9%
Other values (39)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
18
 
7.5%
29
 
8.4%
32
 
1.9%
47
 
6.5%
ValueCountFrequency (%)
4021
0.9%
2481
0.9%
1921
0.9%
1841
0.9%
1751
0.9%

CGD MONTBELIARD
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean34.98058252
Minimum0
Maximum487
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:35.882478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q331
95-th percentile185.1
Maximum487
Range487
Interquartile range (IQR)30

Descriptive statistics

Standard deviation73.3872325
Coefficient of variation (CV)2.097941978
Kurtosis16.73563264
Mean34.98058252
Median Absolute Deviation (MAD)7
Skewness3.710226286
Sum3603
Variance5385.685894
MonotocityNot monotonic
2021-02-18T22:38:35.987505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
024
22.4%
111
 
10.3%
44
 
3.7%
24
 
3.7%
54
 
3.7%
164
 
3.7%
33
 
2.8%
113
 
2.8%
202
 
1.9%
92
 
1.9%
Other values (39)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
111
10.3%
24
 
3.7%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
4871
0.9%
3461
0.9%
2241
0.9%
2051
0.9%
1971
0.9%

CGD PONTARLIER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.18446602
Minimum0
Maximum363
Zeros42
Zeros (%)39.3%
Memory size984.0 B
2021-02-18T22:38:36.084928image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q320
95-th percentile107.6
Maximum363
Range363
Interquartile range (IQR)20

Descriptive statistics

Standard deviation49.87469545
Coefficient of variation (CV)2.151211739
Kurtosis22.47223447
Mean23.18446602
Median Absolute Deviation (MAD)3
Skewness4.166594758
Sum2388
Variance2487.485247
MonotocityNot monotonic
2021-02-18T22:38:36.179209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
042
39.3%
14
 
3.7%
84
 
3.7%
23
 
2.8%
203
 
2.8%
193
 
2.8%
43
 
2.8%
33
 
2.8%
242
 
1.9%
282
 
1.9%
Other values (29)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
042
39.3%
14
 
3.7%
23
 
2.8%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
3631
0.9%
2081
0.9%
1471
0.9%
1431
0.9%
1211
0.9%

CGD CREST
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean34.94174757
Minimum0
Maximum340
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:36.282189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q330
95-th percentile201.1
Maximum340
Range340
Interquartile range (IQR)30

Descriptive statistics

Standard deviation67.20174852
Coefficient of variation (CV)1.92325093
Kurtosis7.050140012
Mean34.94174757
Median Absolute Deviation (MAD)5
Skewness2.675944165
Sum3599
Variance4516.075005
MonotocityNot monotonic
2021-02-18T22:38:36.380801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
027
25.2%
111
 
10.3%
27
 
6.5%
173
 
2.8%
153
 
2.8%
33
 
2.8%
53
 
2.8%
123
 
2.8%
92
 
1.9%
202
 
1.9%
Other values (36)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
111
10.3%
27
 
6.5%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
3401
0.9%
2821
0.9%
2751
0.9%
2111
0.9%
2081
0.9%

CGD NYONS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct32
Distinct (%)31.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean10.52427184
Minimum0
Maximum131
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:36.476844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310
95-th percentile50.6
Maximum131
Range131
Interquartile range (IQR)10

Descriptive statistics

Standard deviation21.27174535
Coefficient of variation (CV)2.021208276
Kurtosis13.28430541
Mean10.52427184
Median Absolute Deviation (MAD)2
Skewness3.388454816
Sum1084
Variance452.4871502
MonotocityNot monotonic
2021-02-18T22:38:36.571417image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
036
33.6%
211
 
10.3%
18
 
7.5%
36
 
5.6%
64
 
3.7%
44
 
3.7%
103
 
2.8%
52
 
1.9%
112
 
1.9%
192
 
1.9%
Other values (22)25
23.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
18
 
7.5%
211
 
10.3%
36
 
5.6%
44
 
3.7%
ValueCountFrequency (%)
1311
0.9%
971
0.9%
871
0.9%
661
0.9%
561
0.9%

CGD PIERRELATTE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.67961165
Minimum0
Maximum268
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:38:36.666554image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q324
95-th percentile159.5
Maximum268
Range268
Interquartile range (IQR)24

Descriptive statistics

Standard deviation50.77829813
Coefficient of variation (CV)1.903262266
Kurtosis7.148895141
Mean26.67961165
Median Absolute Deviation (MAD)5
Skewness2.664805441
Sum2748
Variance2578.435561
MonotocityNot monotonic
2021-02-18T22:38:36.779258image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
25
 
4.7%
74
 
3.7%
114
 
3.7%
93
 
2.8%
243
 
2.8%
32
 
1.9%
332
 
1.9%
62
 
1.9%
Other values (33)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
25
 
4.7%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
2681
0.9%
2051
0.9%
1801
0.9%
1661
0.9%
1641
0.9%

CGD ROMANS SUR ISERE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean40.06796117
Minimum0
Maximum384
Zeros23
Zeros (%)21.5%
Memory size984.0 B
2021-02-18T22:38:36.920421image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q338
95-th percentile228.9
Maximum384
Range384
Interquartile range (IQR)37

Descriptive statistics

Standard deviation74.80225724
Coefficient of variation (CV)1.86688454
Kurtosis6.304175003
Mean40.06796117
Median Absolute Deviation (MAD)6
Skewness2.529188881
Sum4127
Variance5595.377689
MonotocityNot monotonic
2021-02-18T22:38:37.030364image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
023
21.5%
114
 
13.1%
28
 
7.5%
64
 
3.7%
53
 
2.8%
443
 
2.8%
92
 
1.9%
212
 
1.9%
42
 
1.9%
192
 
1.9%
Other values (37)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
023
21.5%
114
13.1%
28
 
7.5%
31
 
0.9%
42
 
1.9%
ValueCountFrequency (%)
3841
0.9%
2881
0.9%
2761
0.9%
2581
0.9%
2391
0.9%

CGD BERNAY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.82524272
Minimum0
Maximum329
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:38:37.133533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q327
95-th percentile142.4
Maximum329
Range329
Interquartile range (IQR)27

Descriptive statistics

Standard deviation54.1945347
Coefficient of variation (CV)1.880106795
Kurtosis10.5370328
Mean28.82524272
Median Absolute Deviation (MAD)4
Skewness2.944106452
Sum2969
Variance2937.047592
MonotocityNot monotonic
2021-02-18T22:38:37.226743image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
031
29.0%
18
 
7.5%
28
 
7.5%
34
 
3.7%
63
 
2.8%
53
 
2.8%
143
 
2.8%
163
 
2.8%
252
 
1.9%
602
 
1.9%
Other values (30)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
18
 
7.5%
28
 
7.5%
34
 
3.7%
41
 
0.9%
ValueCountFrequency (%)
3291
0.9%
2301
0.9%
1751
0.9%
1641
0.9%
1471
0.9%

CGD EVREUX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean31.76699029
Minimum0
Maximum343
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:38:37.326769image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q333
95-th percentile141.9
Maximum343
Range343
Interquartile range (IQR)32

Descriptive statistics

Standard deviation61.24351969
Coefficient of variation (CV)1.927898083
Kurtosis10.70459873
Mean31.76699029
Median Absolute Deviation (MAD)6
Skewness3.067515453
Sum3272
Variance3750.768704
MonotocityNot monotonic
2021-02-18T22:38:37.423897image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
025
23.4%
115
14.0%
27
 
6.5%
114
 
3.7%
73
 
2.8%
93
 
2.8%
143
 
2.8%
362
 
1.9%
32
 
1.9%
62
 
1.9%
Other values (34)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
115
14.0%
27
 
6.5%
32
 
1.9%
51
 
0.9%
ValueCountFrequency (%)
3431
0.9%
2881
0.9%
2811
0.9%
1741
0.9%
1551
0.9%

CGD LES ANDELYS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean31.27184466
Minimum0
Maximum332
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:37.526317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q329
95-th percentile139.1
Maximum332
Range332
Interquartile range (IQR)29

Descriptive statistics

Standard deviation60.04625573
Coefficient of variation (CV)1.920137951
Kurtosis9.505553329
Mean31.27184466
Median Absolute Deviation (MAD)6
Skewness2.945425372
Sum3221
Variance3605.552827
MonotocityNot monotonic
2021-02-18T22:38:37.622310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
027
25.2%
19
 
8.4%
27
 
6.5%
64
 
3.7%
124
 
3.7%
104
 
3.7%
212
 
1.9%
52
 
1.9%
132
 
1.9%
372
 
1.9%
Other values (34)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
19
 
8.4%
27
 
6.5%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
3321
0.9%
2791
0.9%
2421
0.9%
1951
0.9%
1851
0.9%

CGD LOUVIERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.96116505
Minimum0
Maximum323
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:37.720481image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q324
95-th percentile151.9
Maximum323
Range323
Interquartile range (IQR)24

Descriptive statistics

Standard deviation56.20985231
Coefficient of variation (CV)1.940869858
Kurtosis9.570550482
Mean28.96116505
Median Absolute Deviation (MAD)6
Skewness2.926172136
Sum2983
Variance3159.547497
MonotocityNot monotonic
2021-02-18T22:38:37.814985image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
75
 
4.7%
64
 
3.7%
243
 
2.8%
143
 
2.8%
23
 
2.8%
513
 
2.8%
122
 
1.9%
92
 
1.9%
Other values (30)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
23
 
2.8%
32
 
1.9%
41
 
0.9%
ValueCountFrequency (%)
3231
0.9%
2501
0.9%
1941
0.9%
1741
0.9%
1611
0.9%

CGD PONT AUDEMER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.69902913
Minimum0
Maximum288
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:37.915101image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q324.5
95-th percentile131.3
Maximum288
Range288
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation51.48725998
Coefficient of variation (CV)2.003471015
Kurtosis12.34706562
Mean25.69902913
Median Absolute Deviation (MAD)4
Skewness3.304329186
Sum2647
Variance2650.93794
MonotocityNot monotonic
2021-02-18T22:38:38.577640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
033
30.8%
27
 
6.5%
16
 
5.6%
44
 
3.7%
63
 
2.8%
33
 
2.8%
172
 
1.9%
182
 
1.9%
92
 
1.9%
252
 
1.9%
Other values (33)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
16
 
5.6%
27
 
6.5%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
2881
0.9%
2781
0.9%
2031
0.9%
1471
0.9%
1381
0.9%

CGD CHATEAUDUN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.66019417
Minimum0
Maximum216
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:38:38.697138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q324.5
95-th percentile90.6
Maximum216
Range216
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation37.93377961
Coefficient of variation (CV)1.929471259
Kurtosis13.2312745
Mean19.66019417
Median Absolute Deviation (MAD)3
Skewness3.380869973
Sum2025
Variance1438.971635
MonotocityNot monotonic
2021-02-18T22:38:38.823469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
26
 
5.6%
34
 
3.7%
124
 
3.7%
44
 
3.7%
263
 
2.8%
83
 
2.8%
302
 
1.9%
62
 
1.9%
Other values (30)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
26
 
5.6%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
2161
0.9%
2071
0.9%
1611
0.9%
1001
0.9%
951
0.9%

CGD DREUX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean24.00970874
Minimum0
Maximum283
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:38.949295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q320
95-th percentile113.8
Maximum283
Range283
Interquartile range (IQR)20

Descriptive statistics

Standard deviation46.16158643
Coefficient of variation (CV)1.922621675
Kurtosis11.19020818
Mean24.00970874
Median Absolute Deviation (MAD)4
Skewness3.042314096
Sum2473
Variance2130.892062
MonotocityNot monotonic
2021-02-18T22:38:39.048023image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
028
26.2%
111
 
10.3%
28
 
7.5%
34
 
3.7%
94
 
3.7%
44
 
3.7%
163
 
2.8%
172
 
1.9%
62
 
1.9%
282
 
1.9%
Other values (31)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
111
 
10.3%
28
 
7.5%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
2831
0.9%
1921
0.9%
1711
0.9%
1271
0.9%
1241
0.9%

CGD LUCE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.78640777
Minimum0
Maximum336
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:38:39.145153image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q324.5
95-th percentile135.8
Maximum336
Range336
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation55.81019137
Coefficient of variation (CV)2.008542876
Kurtosis12.35274707
Mean27.78640777
Median Absolute Deviation (MAD)4
Skewness3.24518078
Sum2862
Variance3114.77746
MonotocityNot monotonic
2021-02-18T22:38:39.242434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
025
23.4%
116
15.0%
35
 
4.7%
54
 
3.7%
44
 
3.7%
254
 
3.7%
63
 
2.8%
83
 
2.8%
202
 
1.9%
72
 
1.9%
Other values (33)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
116
15.0%
22
 
1.9%
35
 
4.7%
44
 
3.7%
ValueCountFrequency (%)
3361
0.9%
2711
0.9%
2091
0.9%
1421
0.9%
1391
0.9%

CGD NOGENT LE ROTROU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean13.6407767
Minimum0
Maximum178
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:39.340548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q313.5
95-th percentile70.9
Maximum178
Range178
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation29.30898757
Coefficient of variation (CV)2.148630405
Kurtosis16.87506745
Mean13.6407767
Median Absolute Deviation (MAD)2
Skewness3.794505112
Sum1405
Variance859.0167523
MonotocityNot monotonic
2021-02-18T22:38:39.430000image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
037
34.6%
110
 
9.3%
37
 
6.5%
25
 
4.7%
44
 
3.7%
103
 
2.8%
63
 
2.8%
233
 
2.8%
72
 
1.9%
52
 
1.9%
Other values (24)27
25.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
110
 
9.3%
25
 
4.7%
37
 
6.5%
44
 
3.7%
ValueCountFrequency (%)
1781
0.9%
1701
0.9%
871
0.9%
811
0.9%
731
0.9%

CGD BREST
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean37.67961165
Minimum0
Maximum575
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:38:39.532993image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q329.5
95-th percentile170.6
Maximum575
Range575
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation78.92254997
Coefficient of variation (CV)2.094569092
Kurtosis21.71512799
Mean37.67961165
Median Absolute Deviation (MAD)6
Skewness4.041349094
Sum3881
Variance6228.768894
MonotocityNot monotonic
2021-02-18T22:38:39.632818image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
029
27.1%
19
 
8.4%
25
 
4.7%
44
 
3.7%
33
 
2.8%
93
 
2.8%
163
 
2.8%
232
 
1.9%
172
 
1.9%
312
 
1.9%
Other values (40)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
19
 
8.4%
25
 
4.7%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
5751
0.9%
2811
0.9%
2531
0.9%
2321
0.9%
2211
0.9%

CGD CHATEAULIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.80582524
Minimum0
Maximum362
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:39.732559image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q325
95-th percentile124.1
Maximum362
Range362
Interquartile range (IQR)25

Descriptive statistics

Standard deviation52.97947406
Coefficient of variation (CV)2.05300445
Kurtosis17.1353359
Mean25.80582524
Median Absolute Deviation (MAD)4
Skewness3.653890552
Sum2658
Variance2806.824672
MonotocityNot monotonic
2021-02-18T22:38:39.825825image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
35
 
4.7%
24
 
3.7%
104
 
3.7%
83
 
2.8%
63
 
2.8%
593
 
2.8%
43
 
2.8%
362
 
1.9%
Other values (28)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
24
 
3.7%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
3621
0.9%
2141
0.9%
1741
0.9%
1561
0.9%
1511
0.9%

CGD LANDERNEAU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean18.15533981
Minimum0
Maximum230
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:39.922052image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q317.5
95-th percentile96
Maximum230
Range230
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation36.96282109
Coefficient of variation (CV)2.035920092
Kurtosis13.09220168
Mean18.15533981
Median Absolute Deviation (MAD)3
Skewness3.33936758
Sum1870
Variance1366.250143
MonotocityNot monotonic
2021-02-18T22:38:40.014220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
036
33.6%
112
 
11.2%
54
 
3.7%
84
 
3.7%
23
 
2.8%
153
 
2.8%
33
 
2.8%
43
 
2.8%
262
 
1.9%
282
 
1.9%
Other values (27)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
112
 
11.2%
23
 
2.8%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
2301
0.9%
1671
0.9%
1281
0.9%
1161
0.9%
1081
0.9%

CGD PLOURIN LES MORLAIX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean24.51456311
Minimum0
Maximum318
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:40.123048image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q321
95-th percentile113.3
Maximum318
Range318
Interquartile range (IQR)21

Descriptive statistics

Standard deviation48.91045521
Coefficient of variation (CV)1.995159163
Kurtosis14.92407734
Mean24.51456311
Median Absolute Deviation (MAD)3
Skewness3.464467418
Sum2525
Variance2392.232629
MonotocityNot monotonic
2021-02-18T22:38:40.249529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
028
26.2%
115
14.0%
27
 
6.5%
54
 
3.7%
213
 
2.8%
153
 
2.8%
122
 
1.9%
32
 
1.9%
162
 
1.9%
142
 
1.9%
Other values (29)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
115
14.0%
27
 
6.5%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
3181
0.9%
2271
0.9%
1491
0.9%
1451
0.9%
1351
0.9%

CGD QUIMPER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean38.75728155
Minimum0
Maximum511
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:40.361609image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q332
95-th percentile218.8
Maximum511
Range511
Interquartile range (IQR)31

Descriptive statistics

Standard deviation80.37881708
Coefficient of variation (CV)2.073902345
Kurtosis13.70184953
Mean38.75728155
Median Absolute Deviation (MAD)3
Skewness3.393460448
Sum3992
Variance6460.754236
MonotocityNot monotonic
2021-02-18T22:38:40.463178image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
024
22.4%
115
 
14.0%
27
 
6.5%
36
 
5.6%
83
 
2.8%
802
 
1.9%
472
 
1.9%
212
 
1.9%
52
 
1.9%
282
 
1.9%
Other values (34)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
115
14.0%
27
 
6.5%
36
 
5.6%
41
 
0.9%
ValueCountFrequency (%)
5111
0.9%
3271
0.9%
2961
0.9%
2711
0.9%
2291
0.9%

CGD QUIMPERLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.76699029
Minimum0
Maximum324
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:40.560243image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q320
95-th percentile117
Maximum324
Range324
Interquartile range (IQR)20

Descriptive statistics

Standard deviation48.04842408
Coefficient of variation (CV)2.110442508
Kurtosis17.28177629
Mean22.76699029
Median Absolute Deviation (MAD)2
Skewness3.727509336
Sum2345
Variance2308.651057
MonotocityNot monotonic
2021-02-18T22:38:40.652245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
033
30.8%
114
13.1%
26
 
5.6%
35
 
4.7%
83
 
2.8%
132
 
1.9%
102
 
1.9%
632
 
1.9%
202
 
1.9%
192
 
1.9%
Other values (28)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
114
13.1%
26
 
5.6%
35
 
4.7%
41
 
0.9%
ValueCountFrequency (%)
3241
0.9%
2091
0.9%
1781
0.9%
1331
0.9%
1221
0.9%

CGD AJACCIO
Real number (ℝ≥0)

MISSING
ZEROS

Distinct35
Distinct (%)34.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean14.15533981
Minimum0
Maximum207
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:38:40.750124image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q313
95-th percentile67.5
Maximum207
Range207
Interquartile range (IQR)13

Descriptive statistics

Standard deviation29.08734557
Coefficient of variation (CV)2.054867348
Kurtosis20.32584432
Mean14.15533981
Median Absolute Deviation (MAD)3
Skewness3.959651128
Sum1458
Variance846.0736722
MonotocityNot monotonic
2021-02-18T22:38:40.838885image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
038
35.5%
113
 
12.1%
45
 
4.7%
75
 
4.7%
83
 
2.8%
133
 
2.8%
33
 
2.8%
92
 
1.9%
292
 
1.9%
112
 
1.9%
Other values (25)27
25.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
113
 
12.1%
33
 
2.8%
45
 
4.7%
62
 
1.9%
ValueCountFrequency (%)
2071
0.9%
1201
0.9%
991
0.9%
781
0.9%
751
0.9%

CGD PORTO VECCHIO
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean14.90291262
Minimum0
Maximum180
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:40.930398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q316
95-th percentile79.2
Maximum180
Range180
Interquartile range (IQR)16

Descriptive statistics

Standard deviation29.68313529
Coefficient of variation (CV)1.991767385
Kurtosis14.86978435
Mean14.90291262
Median Absolute Deviation (MAD)2
Skewness3.555039095
Sum1535
Variance881.0885208
MonotocityNot monotonic
2021-02-18T22:38:41.022678image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
028
26.2%
117
15.9%
27
 
6.5%
33
 
2.8%
63
 
2.8%
43
 
2.8%
163
 
2.8%
53
 
2.8%
82
 
1.9%
332
 
1.9%
Other values (26)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
117
15.9%
27
 
6.5%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
1801
0.9%
1631
0.9%
951
0.9%
841
0.9%
802
1.9%

CGD SARTENE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct27
Distinct (%)26.2%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean7.184466019
Minimum0
Maximum99
Zeros43
Zeros (%)40.2%
Memory size984.0 B
2021-02-18T22:38:41.117895image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36.5
95-th percentile33.8
Maximum99
Range99
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation14.50608228
Coefficient of variation (CV)2.01908983
Kurtosis16.92904121
Mean7.184466019
Median Absolute Deviation (MAD)1
Skewness3.61362058
Sum740
Variance210.426423
MonotocityNot monotonic
2021-02-18T22:38:41.208963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
043
40.2%
110
 
9.3%
210
 
9.3%
36
 
5.6%
54
 
3.7%
173
 
2.8%
123
 
2.8%
142
 
1.9%
72
 
1.9%
62
 
1.9%
Other values (17)18
16.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
043
40.2%
110
 
9.3%
210
 
9.3%
36
 
5.6%
42
 
1.9%
ValueCountFrequency (%)
991
0.9%
581
0.9%
521
0.9%
401
0.9%
361
0.9%

CGD BASTIA
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean18.06796117
Minimum0
Maximum197
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:41.337631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q318
95-th percentile83.8
Maximum197
Range197
Interquartile range (IQR)18

Descriptive statistics

Standard deviation33.59454383
Coefficient of variation (CV)1.859343372
Kurtosis10.84236936
Mean18.06796117
Median Absolute Deviation (MAD)4
Skewness3.025187558
Sum1861
Variance1128.593375
MonotocityNot monotonic
2021-02-18T22:38:41.465040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
033
30.8%
111
 
10.3%
46
 
5.6%
33
 
2.8%
83
 
2.8%
63
 
2.8%
413
 
2.8%
122
 
1.9%
132
 
1.9%
182
 
1.9%
Other values (30)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
111
 
10.3%
22
 
1.9%
33
 
2.8%
46
 
5.6%
ValueCountFrequency (%)
1971
0.9%
1661
0.9%
1071
0.9%
971
0.9%
891
0.9%

CGD CALVI
Real number (ℝ≥0)

MISSING
ZEROS

Distinct29
Distinct (%)28.2%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean9.155339806
Minimum0
Maximum98
Zeros39
Zeros (%)36.4%
Memory size984.0 B
2021-02-18T22:38:41.569281image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310
95-th percentile42.5
Maximum98
Range98
Interquartile range (IQR)10

Descriptive statistics

Standard deviation18.13930695
Coefficient of variation (CV)1.981281671
Kurtosis11.16912423
Mean9.155339806
Median Absolute Deviation (MAD)2
Skewness3.234015924
Sum943
Variance329.0344565
MonotocityNot monotonic
2021-02-18T22:38:41.657592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
039
36.4%
110
 
9.3%
38
 
7.5%
45
 
4.7%
54
 
3.7%
104
 
3.7%
23
 
2.8%
73
 
2.8%
132
 
1.9%
92
 
1.9%
Other values (19)23
21.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
039
36.4%
110
 
9.3%
23
 
2.8%
38
 
7.5%
45
 
4.7%
ValueCountFrequency (%)
981
0.9%
881
0.9%
841
0.9%
601
0.9%
591
0.9%

CGD CORTE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct19
Distinct (%)18.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean4.223300971
Minimum0
Maximum60
Zeros43
Zeros (%)40.2%
Memory size984.0 B
2021-02-18T22:38:41.743605image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile26.8
Maximum60
Range60
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.182178005
Coefficient of variation (CV)2.174170884
Kurtosis15.64200332
Mean4.223300971
Median Absolute Deviation (MAD)1
Skewness3.648596833
Sum435
Variance84.31239292
MonotocityNot monotonic
2021-02-18T22:38:41.821342image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
043
40.2%
123
21.5%
47
 
6.5%
25
 
4.7%
34
 
3.7%
92
 
1.9%
52
 
1.9%
72
 
1.9%
272
 
1.9%
102
 
1.9%
Other values (9)11
 
10.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
043
40.2%
123
21.5%
25
 
4.7%
34
 
3.7%
47
 
6.5%
ValueCountFrequency (%)
601
0.9%
381
0.9%
331
0.9%
291
0.9%
272
1.9%

CGD GHISONACCIA
Real number (ℝ≥0)

MISSING
ZEROS

Distinct23
Distinct (%)22.3%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean7.893203883
Minimum0
Maximum111
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:41.907581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q37.5
95-th percentile39
Maximum111
Range111
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation15.90591986
Coefficient of variation (CV)2.015141139
Kurtosis19.04621965
Mean7.893203883
Median Absolute Deviation (MAD)2
Skewness3.84201616
Sum813
Variance252.9982867
MonotocityNot monotonic
2021-02-18T22:38:41.988623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
037
34.6%
111
 
10.3%
210
 
9.3%
36
 
5.6%
66
 
5.6%
154
 
3.7%
303
 
2.8%
53
 
2.8%
43
 
2.8%
393
 
2.8%
Other values (13)17
15.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
111
 
10.3%
210
 
9.3%
36
 
5.6%
43
 
2.8%
ValueCountFrequency (%)
1111
 
0.9%
721
 
0.9%
411
 
0.9%
401
 
0.9%
393
2.8%

CGD ALES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean39.61165049
Minimum0
Maximum445
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:38:42.085543image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q328.5
95-th percentile212.4
Maximum445
Range445
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation79.5621884
Coefficient of variation (CV)2.008555246
Kurtosis9.53492124
Mean39.61165049
Median Absolute Deviation (MAD)7
Skewness2.985033104
Sum4080
Variance6330.141824
MonotocityNot monotonic
2021-02-18T22:38:42.182674image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
025
23.4%
110
 
9.3%
28
 
7.5%
35
 
4.7%
73
 
2.8%
302
 
1.9%
192
 
1.9%
92
 
1.9%
172
 
1.9%
122
 
1.9%
Other values (37)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
110
 
9.3%
28
 
7.5%
35
 
4.7%
42
 
1.9%
ValueCountFrequency (%)
4451
0.9%
3461
0.9%
2892
1.9%
2731
0.9%
2171
0.9%

CGD BAGNOLS SUR CEZE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean36.03883495
Minimum0
Maximum405
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:42.282553image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q326.5
95-th percentile230.9
Maximum405
Range405
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation73.42889349
Coefficient of variation (CV)2.037493542
Kurtosis9.252111909
Mean36.03883495
Median Absolute Deviation (MAD)8
Skewness3.004054294
Sum3712
Variance5391.802399
MonotocityNot monotonic
2021-02-18T22:38:42.383841image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
028
26.2%
112
 
11.2%
303
 
2.8%
173
 
2.8%
23
 
2.8%
103
 
2.8%
123
 
2.8%
163
 
2.8%
73
 
2.8%
1312
 
1.9%
Other values (34)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
112
11.2%
23
 
2.8%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
4051
0.9%
2951
0.9%
2771
0.9%
2651
0.9%
2561
0.9%

CGD LE VIGAN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean13.59223301
Minimum0
Maximum117
Zeros44
Zeros (%)41.1%
Memory size984.0 B
2021-02-18T22:38:42.482775image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q313.5
95-th percentile70.4
Maximum117
Range117
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation24.0316119
Coefficient of variation (CV)1.768040018
Kurtosis5.156385751
Mean13.59223301
Median Absolute Deviation (MAD)2
Skewness2.298194421
Sum1400
Variance577.5183705
MonotocityNot monotonic
2021-02-18T22:38:42.579689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
044
41.1%
17
 
6.5%
26
 
5.6%
133
 
2.8%
83
 
2.8%
33
 
2.8%
52
 
1.9%
122
 
1.9%
42
 
1.9%
92
 
1.9%
Other values (24)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
044
41.1%
17
 
6.5%
26
 
5.6%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
1171
0.9%
1011
0.9%
832
1.9%
731
0.9%
711
0.9%

CGD NIMES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean48.23300971
Minimum0
Maximum600
Zeros22
Zeros (%)20.6%
Memory size984.0 B
2021-02-18T22:38:42.715116image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q331
95-th percentile276.8
Maximum600
Range600
Interquartile range (IQR)30

Descriptive statistics

Standard deviation100.8102667
Coefficient of variation (CV)2.09006793
Kurtosis11.99851388
Mean48.23300971
Median Absolute Deviation (MAD)8
Skewness3.263245096
Sum4968
Variance10162.70988
MonotocityNot monotonic
2021-02-18T22:38:42.831701image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
022
20.6%
112
 
11.2%
310
 
9.3%
283
 
2.8%
23
 
2.8%
293
 
2.8%
43
 
2.8%
312
 
1.9%
262
 
1.9%
132
 
1.9%
Other values (37)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
022
20.6%
112
11.2%
23
 
2.8%
310
9.3%
43
 
2.8%
ValueCountFrequency (%)
6001
0.9%
4771
0.9%
3591
0.9%
2991
0.9%
2931
0.9%

CGD VAUVERT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean47.2815534
Minimum0
Maximum487
Zeros22
Zeros (%)20.6%
Memory size984.0 B
2021-02-18T22:38:42.938171image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10
Q337.5
95-th percentile286.8
Maximum487
Range487
Interquartile range (IQR)36.5

Descriptive statistics

Standard deviation96.38234903
Coefficient of variation (CV)2.038476787
Kurtosis9.479312039
Mean47.2815534
Median Absolute Deviation (MAD)10
Skewness3.077787041
Sum4870
Variance9289.557205
MonotocityNot monotonic
2021-02-18T22:38:43.044770image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
022
20.6%
112
 
11.2%
37
 
6.5%
25
 
4.7%
283
 
2.8%
113
 
2.8%
323
 
2.8%
92
 
1.9%
232
 
1.9%
102
 
1.9%
Other values (39)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
022
20.6%
112
11.2%
25
 
4.7%
37
 
6.5%
41
 
0.9%
ValueCountFrequency (%)
4871
0.9%
4501
0.9%
4111
0.9%
3601
0.9%
3501
0.9%

CGD MURET
Real number (ℝ≥0)

MISSING
ZEROS

Distinct54
Distinct (%)52.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean70.30097087
Minimum0
Maximum892
Zeros23
Zeros (%)21.5%
Memory size984.0 B
2021-02-18T22:38:43.150575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10
Q359
95-th percentile376.7
Maximum892
Range892
Interquartile range (IQR)58

Descriptive statistics

Standard deviation146.7626358
Coefficient of variation (CV)2.087633129
Kurtosis13.21919196
Mean70.30097087
Median Absolute Deviation (MAD)10
Skewness3.41019201
Sum7241
Variance21539.27127
MonotocityNot monotonic
2021-02-18T22:38:43.251098image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
023
21.5%
38
 
7.5%
15
 
4.7%
25
 
4.7%
44
 
3.7%
63
 
2.8%
53
 
2.8%
233
 
2.8%
172
 
1.9%
132
 
1.9%
Other values (44)45
42.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
023
21.5%
15
 
4.7%
25
 
4.7%
38
 
7.5%
44
 
3.7%
ValueCountFrequency (%)
8921
0.9%
6771
0.9%
6061
0.9%
4441
0.9%
4271
0.9%

CGD ST GAUDENS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean18.7961165
Minimum0
Maximum223
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:38:43.349601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q317.5
95-th percentile85.6
Maximum223
Range223
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation37.05410967
Coefficient of variation (CV)1.971370504
Kurtosis11.39500424
Mean18.7961165
Median Absolute Deviation (MAD)2
Skewness3.11487292
Sum1936
Variance1373.007044
MonotocityNot monotonic
2021-02-18T22:38:43.439048image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
038
35.5%
112
 
11.2%
35
 
4.7%
64
 
3.7%
153
 
2.8%
73
 
2.8%
103
 
2.8%
732
 
1.9%
342
 
1.9%
22
 
1.9%
Other values (26)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
112
 
11.2%
22
 
1.9%
35
 
4.7%
41
 
0.9%
ValueCountFrequency (%)
2231
0.9%
1581
0.9%
1481
0.9%
1251
0.9%
911
0.9%

CGD TOULOUSE MIRAIL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct51
Distinct (%)49.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean69.76699029
Minimum0
Maximum845
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:43.539056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q348
95-th percentile469.1
Maximum845
Range845
Interquartile range (IQR)47

Descriptive statistics

Standard deviation154.4199268
Coefficient of variation (CV)2.213366611
Kurtosis12.04170961
Mean69.76699029
Median Absolute Deviation (MAD)7
Skewness3.37500056
Sum7186
Variance23845.5138
MonotocityNot monotonic
2021-02-18T22:38:43.638986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
024
22.4%
110
 
9.3%
28
 
7.5%
33
 
2.8%
53
 
2.8%
182
 
1.9%
222
 
1.9%
342
 
1.9%
92
 
1.9%
262
 
1.9%
Other values (41)45
42.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
110
9.3%
28
 
7.5%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
8451
0.9%
7991
0.9%
5861
0.9%
5221
0.9%
4991
0.9%

CGD TOULOUSE ST MICHEL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct55
Distinct (%)53.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean90.45631068
Minimum0
Maximum1459
Zeros22
Zeros (%)20.6%
Memory size984.0 B
2021-02-18T22:38:43.748588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10
Q362
95-th percentile498.9
Maximum1459
Range1459
Interquartile range (IQR)61

Descriptive statistics

Standard deviation209.181963
Coefficient of variation (CV)2.312519287
Kurtosis20.7744753
Mean90.45631068
Median Absolute Deviation (MAD)10
Skewness4.127746502
Sum9317
Variance43757.09366
MonotocityNot monotonic
2021-02-18T22:38:43.852251image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
022
20.6%
36
 
5.6%
16
 
5.6%
74
 
3.7%
24
 
3.7%
43
 
2.8%
123
 
2.8%
442
 
1.9%
252
 
1.9%
102
 
1.9%
Other values (45)49
45.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
022
20.6%
16
 
5.6%
24
 
3.7%
36
 
5.6%
43
 
2.8%
ValueCountFrequency (%)
14591
0.9%
9701
0.9%
6611
0.9%
6481
0.9%
5311
0.9%

CGD VILLEFRANCHE DE LAURAGAIS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean65.74757282
Minimum0
Maximum917
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:43.959642image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q340
95-th percentile357
Maximum917
Range917
Interquartile range (IQR)40

Descriptive statistics

Standard deviation152.1824059
Coefficient of variation (CV)2.314646753
Kurtosis14.85743181
Mean65.74757282
Median Absolute Deviation (MAD)8
Skewness3.681427155
Sum6772
Variance23159.48468
MonotocityNot monotonic
2021-02-18T22:38:44.060050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
028
26.2%
17
 
6.5%
26
 
5.6%
85
 
4.7%
93
 
2.8%
43
 
2.8%
262
 
1.9%
202
 
1.9%
1112
 
1.9%
72
 
1.9%
Other values (37)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
17
 
6.5%
26
 
5.6%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
9171
0.9%
7731
0.9%
5541
0.9%
5191
0.9%
5111
0.9%

CGD AUCH
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.12621359
Minimum0
Maximum347
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:44.157721image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q318.5
95-th percentile112.7
Maximum347
Range347
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation49.15734633
Coefficient of variation (CV)2.125611533
Kurtosis19.68842353
Mean23.12621359
Median Absolute Deviation (MAD)3
Skewness3.90942954
Sum2382
Variance2416.444698
MonotocityNot monotonic
2021-02-18T22:38:44.254288image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
033
30.8%
111
 
10.3%
26
 
5.6%
153
 
2.8%
33
 
2.8%
93
 
2.8%
72
 
1.9%
112
 
1.9%
402
 
1.9%
42
 
1.9%
Other values (31)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
111
 
10.3%
26
 
5.6%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
3471
0.9%
1951
0.9%
1581
0.9%
1481
0.9%
1361
0.9%

CGD CONDOM
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.73786408
Minimum0
Maximum277
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:44.355011image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q321
95-th percentile114.8
Maximum277
Range277
Interquartile range (IQR)21

Descriptive statistics

Standard deviation46.83260997
Coefficient of variation (CV)2.05967499
Kurtosis12.61794483
Mean22.73786408
Median Absolute Deviation (MAD)3
Skewness3.339089062
Sum2342
Variance2193.293356
MonotocityNot monotonic
2021-02-18T22:38:44.447510image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
027
25.2%
119
17.8%
34
 
3.7%
104
 
3.7%
23
 
2.8%
222
 
1.9%
162
 
1.9%
92
 
1.9%
532
 
1.9%
342
 
1.9%
Other values (31)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
119
17.8%
23
 
2.8%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
2771
0.9%
2341
0.9%
1751
0.9%
1421
0.9%
1351
0.9%

CGD ARCACHON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean50.58252427
Minimum0
Maximum696
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:38:44.548287image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q344
95-th percentile346.7
Maximum696
Range696
Interquartile range (IQR)43

Descriptive statistics

Standard deviation111.7976572
Coefficient of variation (CV)2.210203204
Kurtosis13.86141604
Mean50.58252427
Median Absolute Deviation (MAD)5
Skewness3.508418543
Sum5210
Variance12498.71616
MonotocityNot monotonic
2021-02-18T22:38:45.475674image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
025
23.4%
110
 
9.3%
56
 
5.6%
25
 
4.7%
34
 
3.7%
263
 
2.8%
43
 
2.8%
193
 
2.8%
902
 
1.9%
322
 
1.9%
Other values (35)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
110
 
9.3%
25
 
4.7%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
6961
0.9%
4941
0.9%
3801
0.9%
3571
0.9%
3551
0.9%

CGD BLAYE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean38.72815534
Minimum0
Maximum374
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:45.585268image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q333
95-th percentile215.7
Maximum374
Range374
Interquartile range (IQR)32

Descriptive statistics

Standard deviation74.81391217
Coefficient of variation (CV)1.931770608
Kurtosis8.157866005
Mean38.72815534
Median Absolute Deviation (MAD)5
Skewness2.803530177
Sum3989
Variance5597.121454
MonotocityNot monotonic
2021-02-18T22:38:45.680063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
024
22.4%
110
 
9.3%
28
 
7.5%
47
 
6.5%
73
 
2.8%
453
 
2.8%
152
 
1.9%
32
 
1.9%
62
 
1.9%
262
 
1.9%
Other values (35)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
110
9.3%
28
 
7.5%
32
 
1.9%
47
 
6.5%
ValueCountFrequency (%)
3741
0.9%
3731
0.9%
2661
0.9%
2561
0.9%
2341
0.9%

CGD BOULIAC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean59.26213592
Minimum0
Maximum798
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:45.786554image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q344.5
95-th percentile297.9
Maximum798
Range798
Interquartile range (IQR)44.5

Descriptive statistics

Standard deviation135.8249999
Coefficient of variation (CV)2.291935615
Kurtosis13.49920154
Mean59.26213592
Median Absolute Deviation (MAD)6
Skewness3.542805612
Sum6104
Variance18448.43061
MonotocityNot monotonic
2021-02-18T22:38:45.892623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
027
25.2%
27
 
6.5%
15
 
4.7%
54
 
3.7%
154
 
3.7%
64
 
3.7%
44
 
3.7%
33
 
2.8%
182
 
1.9%
192
 
1.9%
Other values (39)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
15
 
4.7%
27
 
6.5%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
7981
0.9%
6171
0.9%
5751
0.9%
5621
0.9%
3291
0.9%

CGD LANGON TOULENNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean44.6407767
Minimum0
Maximum507
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:38:45.999436image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median7
Q342.5
95-th percentile253.9
Maximum507
Range507
Interquartile range (IQR)42

Descriptive statistics

Standard deviation91.33807642
Coefficient of variation (CV)2.046068262
Kurtosis10.05966689
Mean44.6407767
Median Absolute Deviation (MAD)7
Skewness3.070761306
Sum4598
Variance8342.644203
MonotocityNot monotonic
2021-02-18T22:38:46.113349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
026
24.3%
111
 
10.3%
44
 
3.7%
34
 
3.7%
84
 
3.7%
24
 
3.7%
183
 
2.8%
422
 
1.9%
472
 
1.9%
52
 
1.9%
Other values (36)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
111
10.3%
24
 
3.7%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
5071
0.9%
4241
0.9%
3501
0.9%
3221
0.9%
2771
0.9%

CGD LESPARRE MEDOC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean47.42718447
Minimum0
Maximum496
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:38:46.250718image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q343
95-th percentile315.7
Maximum496
Range496
Interquartile range (IQR)42

Descriptive statistics

Standard deviation93.71730561
Coefficient of variation (CV)1.976025072
Kurtosis8.801881395
Mean47.42718447
Median Absolute Deviation (MAD)6
Skewness2.923155581
Sum4885
Variance8782.933371
MonotocityNot monotonic
2021-02-18T22:38:46.372837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
025
23.4%
28
 
7.5%
17
 
6.5%
54
 
3.7%
44
 
3.7%
1553
 
2.8%
212
 
1.9%
142
 
1.9%
32
 
1.9%
222
 
1.9%
Other values (38)44
41.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
17
 
6.5%
28
 
7.5%
32
 
1.9%
44
 
3.7%
ValueCountFrequency (%)
4961
0.9%
4171
0.9%
3461
0.9%
3341
0.9%
3331
0.9%

CGD LIBOURNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct54
Distinct (%)52.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean61.77669903
Minimum0
Maximum670
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:46.478577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q346
95-th percentile324.1
Maximum670
Range670
Interquartile range (IQR)45

Descriptive statistics

Standard deviation122.6208033
Coefficient of variation (CV)1.984903779
Kurtosis9.596202907
Mean61.77669903
Median Absolute Deviation (MAD)9
Skewness2.999993123
Sum6363
Variance15035.86141
MonotocityNot monotonic
2021-02-18T22:38:46.581605image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
024
22.4%
17
 
6.5%
84
 
3.7%
24
 
3.7%
93
 
2.8%
73
 
2.8%
112
 
1.9%
42
 
1.9%
432
 
1.9%
372
 
1.9%
Other values (44)50
46.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
17
 
6.5%
24
 
3.7%
31
 
0.9%
42
 
1.9%
ValueCountFrequency (%)
6701
0.9%
5781
0.9%
4451
0.9%
4381
0.9%
4071
0.9%

CGD MERIGNAC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean66.83495146
Minimum0
Maximum921
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:46.689298image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q348.5
95-th percentile381.5
Maximum921
Range921
Interquartile range (IQR)48.5

Descriptive statistics

Standard deviation157.7622993
Coefficient of variation (CV)2.360476006
Kurtosis17.08302807
Mean66.83495146
Median Absolute Deviation (MAD)6
Skewness3.919965742
Sum6884
Variance24888.94308
MonotocityNot monotonic
2021-02-18T22:38:46.790767image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
027
25.2%
26
 
5.6%
16
 
5.6%
54
 
3.7%
214
 
3.7%
44
 
3.7%
33
 
2.8%
63
 
2.8%
222
 
1.9%
1032
 
1.9%
Other values (38)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
16
 
5.6%
26
 
5.6%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
9211
0.9%
9181
0.9%
6291
0.9%
4271
0.9%
3981
0.9%

CGD BEZIERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean42.11650485
Minimum0
Maximum488
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:46.889387image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q334
95-th percentile215
Maximum488
Range488
Interquartile range (IQR)33

Descriptive statistics

Standard deviation87.93427815
Coefficient of variation (CV)2.087881662
Kurtosis10.80025903
Mean42.11650485
Median Absolute Deviation (MAD)5
Skewness3.202141765
Sum4338
Variance7732.437274
MonotocityNot monotonic
2021-02-18T22:38:46.995005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
024
22.4%
19
 
8.4%
27
 
6.5%
36
 
5.6%
44
 
3.7%
103
 
2.8%
782
 
1.9%
222
 
1.9%
72
 
1.9%
162
 
1.9%
Other values (37)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
19
 
8.4%
27
 
6.5%
36
 
5.6%
44
 
3.7%
ValueCountFrequency (%)
4881
0.9%
3881
0.9%
3831
0.9%
3181
0.9%
3051
0.9%

CGD CASTELNAU LE LEZ
Real number (ℝ≥0)

MISSING
ZEROS

Distinct55
Distinct (%)53.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean92.48543689
Minimum0
Maximum972
Zeros18
Zeros (%)16.8%
Memory size984.0 B
2021-02-18T22:38:47.100749image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median13
Q352
95-th percentile539.5
Maximum972
Range972
Interquartile range (IQR)51

Descriptive statistics

Standard deviation196.7979886
Coefficient of variation (CV)2.127880834
Kurtosis8.35976241
Mean92.48543689
Median Absolute Deviation (MAD)13
Skewness2.911988278
Sum9526
Variance38729.44832
MonotocityNot monotonic
2021-02-18T22:38:47.206162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
018
 
16.8%
114
 
13.1%
26
 
5.6%
74
 
3.7%
363
 
2.8%
43
 
2.8%
223
 
2.8%
32
 
1.9%
432
 
1.9%
272
 
1.9%
Other values (45)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
018
16.8%
114
13.1%
26
 
5.6%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
9721
0.9%
9091
0.9%
8281
0.9%
6921
0.9%
5911
0.9%

CGD LODEVE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean34.55339806
Minimum0
Maximum305
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:38:47.307878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q329
95-th percentile224.8
Maximum305
Range305
Interquartile range (IQR)29

Descriptive statistics

Standard deviation66.93408056
Coefficient of variation (CV)1.937120061
Kurtosis6.074181911
Mean34.55339806
Median Absolute Deviation (MAD)4
Skewness2.562164438
Sum3559
Variance4480.17114
MonotocityNot monotonic
2021-02-18T22:38:47.404802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
030
28.0%
110
 
9.3%
26
 
5.6%
34
 
3.7%
44
 
3.7%
73
 
2.8%
173
 
2.8%
292
 
1.9%
192
 
1.9%
582
 
1.9%
Other values (35)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
110
 
9.3%
26
 
5.6%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
3051
0.9%
2751
0.9%
2651
0.9%
2491
0.9%
2381
0.9%

CGD LUNEL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct54
Distinct (%)52.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean69.44660194
Minimum0
Maximum699
Zeros18
Zeros (%)16.8%
Memory size984.0 B
2021-02-18T22:38:47.508916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q352.5
95-th percentile436.1
Maximum699
Range699
Interquartile range (IQR)51.5

Descriptive statistics

Standard deviation150.8778709
Coefficient of variation (CV)2.172573843
Kurtosis9.251328214
Mean69.44660194
Median Absolute Deviation (MAD)9
Skewness3.094556983
Sum7153
Variance22764.13192
MonotocityNot monotonic
2021-02-18T22:38:47.611085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
018
 
16.8%
113
 
12.1%
245
 
4.7%
25
 
4.7%
34
 
3.7%
64
 
3.7%
252
 
1.9%
42
 
1.9%
322
 
1.9%
202
 
1.9%
Other values (44)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
018
16.8%
113
12.1%
25
 
4.7%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
6991
0.9%
6871
0.9%
6641
0.9%
6571
0.9%
4911
0.9%

CGD PEZENAS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct51
Distinct (%)49.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean56.77669903
Minimum0
Maximum636
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:47.719092image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median11
Q340.5
95-th percentile368
Maximum636
Range636
Interquartile range (IQR)39.5

Descriptive statistics

Standard deviation115.9819063
Coefficient of variation (CV)2.042772973
Kurtosis9.1132035
Mean56.77669903
Median Absolute Deviation (MAD)11
Skewness2.969761837
Sum5848
Variance13451.80259
MonotocityNot monotonic
2021-02-18T22:38:47.820400image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
024
22.4%
28
 
7.5%
16
 
5.6%
35
 
4.7%
273
 
2.8%
503
 
2.8%
133
 
2.8%
43
 
2.8%
73
 
2.8%
342
 
1.9%
Other values (41)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
16
 
5.6%
28
 
7.5%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
6361
0.9%
4921
0.9%
4251
0.9%
4111
0.9%
3961
0.9%

CGD MONTFORT SUR MEU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.01941748
Minimum0
Maximum355
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:38:47.922539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q319.5
95-th percentile122.7
Maximum355
Range355
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation53.88858888
Coefficient of variation (CV)2.071091289
Kurtosis17.14814186
Mean26.01941748
Median Absolute Deviation (MAD)4
Skewness3.727323086
Sum2680
Variance2903.980011
MonotocityNot monotonic
2021-02-18T22:38:48.019544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
032
29.9%
18
 
7.5%
28
 
7.5%
45
 
4.7%
133
 
2.8%
153
 
2.8%
183
 
2.8%
33
 
2.8%
552
 
1.9%
142
 
1.9%
Other values (31)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
18
 
7.5%
28
 
7.5%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
3551
0.9%
2731
0.9%
1601
0.9%
1561
0.9%
1381
0.9%

CGD REDON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.32038835
Minimum0
Maximum355
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:38:48.122958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q325
95-th percentile124.2
Maximum355
Range355
Interquartile range (IQR)25

Descriptive statistics

Standard deviation56.12559683
Coefficient of variation (CV)1.98180887
Kurtosis14.41767936
Mean28.32038835
Median Absolute Deviation (MAD)4
Skewness3.429670106
Sum2917
Variance3150.082619
MonotocityNot monotonic
2021-02-18T22:38:48.222908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
031
29.0%
110
 
9.3%
26
 
5.6%
34
 
3.7%
233
 
2.8%
143
 
2.8%
43
 
2.8%
162
 
1.9%
252
 
1.9%
122
 
1.9%
Other values (32)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
110
 
9.3%
26
 
5.6%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
3551
0.9%
2771
0.9%
1801
0.9%
1751
0.9%
1551
0.9%

CGD RENNES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct52
Distinct (%)50.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean67.34951456
Minimum0
Maximum741
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:38:48.353305image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q368
95-th percentile342
Maximum741
Range741
Interquartile range (IQR)67

Descriptive statistics

Standard deviation131.8866647
Coefficient of variation (CV)1.958242247
Kurtosis9.400395457
Mean67.34951456
Median Absolute Deviation (MAD)7
Skewness2.929713398
Sum6937
Variance17394.09233
MonotocityNot monotonic
2021-02-18T22:38:48.476815image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
025
23.4%
110
 
9.3%
24
 
3.7%
34
 
3.7%
83
 
2.8%
43
 
2.8%
73
 
2.8%
112
 
1.9%
542
 
1.9%
192
 
1.9%
Other values (42)45
42.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
110
 
9.3%
24
 
3.7%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
7411
0.9%
5591
0.9%
5071
0.9%
4931
0.9%
4071
0.9%

CGD ST MALO
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.70873786
Minimum0
Maximum327
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:48.584672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q325.5
95-th percentile143.2
Maximum327
Range327
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation54.72957244
Coefficient of variation (CV)1.975173778
Kurtosis11.67001258
Mean27.70873786
Median Absolute Deviation (MAD)4
Skewness3.153808921
Sum2854
Variance2995.326099
MonotocityNot monotonic
2021-02-18T22:38:48.681720image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
037
34.6%
47
 
6.5%
16
 
5.6%
164
 
3.7%
63
 
2.8%
213
 
2.8%
23
 
2.8%
842
 
1.9%
32
 
1.9%
332
 
1.9%
Other values (32)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
16
 
5.6%
23
 
2.8%
32
 
1.9%
47
 
6.5%
ValueCountFrequency (%)
3271
0.9%
2621
0.9%
1791
0.9%
1751
0.9%
1551
0.9%

CGD VITRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean52.41747573
Minimum0
Maximum657
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:38:48.786456image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q351.5
95-th percentile237.7
Maximum657
Range657
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation105.203866
Coefficient of variation (CV)2.007038006
Kurtosis13.35532189
Mean52.41747573
Median Absolute Deviation (MAD)5
Skewness3.339683582
Sum5399
Variance11067.85342
MonotocityNot monotonic
2021-02-18T22:38:48.888344image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
025
23.4%
110
 
9.3%
26
 
5.6%
35
 
4.7%
45
 
4.7%
223
 
2.8%
52
 
1.9%
402
 
1.9%
552
 
1.9%
122
 
1.9%
Other values (39)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
110
 
9.3%
26
 
5.6%
35
 
4.7%
45
 
4.7%
ValueCountFrequency (%)
6571
0.9%
4841
0.9%
3851
0.9%
3311
0.9%
2891
0.9%

CGD ISSOUDUN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean15.09708738
Minimum0
Maximum170
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:38:48.990179image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314
95-th percentile66.2
Maximum170
Range170
Interquartile range (IQR)14

Descriptive statistics

Standard deviation30.22092333
Coefficient of variation (CV)2.001771771
Kurtosis12.93349955
Mean15.09708738
Median Absolute Deviation (MAD)2
Skewness3.338294353
Sum1555
Variance913.3042071
MonotocityNot monotonic
2021-02-18T22:38:49.084255image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
038
35.5%
110
 
9.3%
116
 
5.6%
25
 
4.7%
74
 
3.7%
63
 
2.8%
43
 
2.8%
32
 
1.9%
52
 
1.9%
142
 
1.9%
Other values (27)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
110
 
9.3%
25
 
4.7%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
1701
0.9%
1691
0.9%
1031
0.9%
981
0.9%
801
0.9%

CGD LA CHATRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.62135922
Minimum0
Maximum217
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:38:49.185580image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q316
95-th percentile83
Maximum217
Range217
Interquartile range (IQR)16

Descriptive statistics

Standard deviation35.57817036
Coefficient of variation (CV)2.019036665
Kurtosis13.61576746
Mean17.62135922
Median Absolute Deviation (MAD)2
Skewness3.370931295
Sum1815
Variance1265.806206
MonotocityNot monotonic
2021-02-18T22:38:49.277324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
038
35.5%
19
 
8.4%
37
 
6.5%
25
 
4.7%
303
 
2.8%
93
 
2.8%
62
 
1.9%
832
 
1.9%
122
 
1.9%
112
 
1.9%
Other values (27)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
19
 
8.4%
25
 
4.7%
37
 
6.5%
41
 
0.9%
ValueCountFrequency (%)
2171
0.9%
1831
0.9%
1231
0.9%
941
0.9%
891
0.9%

CGD LE BLANC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct32
Distinct (%)31.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.5631068
Minimum0
Maximum178
Zeros47
Zeros (%)43.9%
Memory size984.0 B
2021-02-18T22:38:49.368646image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q312
95-th percentile64.4
Maximum178
Range178
Interquartile range (IQR)12

Descriptive statistics

Standard deviation24.96140939
Coefficient of variation (CV)1.986881891
Kurtosis19.34860906
Mean12.5631068
Median Absolute Deviation (MAD)2
Skewness3.767858533
Sum1294
Variance623.0719589
MonotocityNot monotonic
2021-02-18T22:38:49.458799image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
047
43.9%
106
 
5.6%
25
 
4.7%
44
 
3.7%
14
 
3.7%
143
 
2.8%
33
 
2.8%
112
 
1.9%
82
 
1.9%
122
 
1.9%
Other values (22)25
23.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
047
43.9%
14
 
3.7%
25
 
4.7%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
1781
0.9%
911
0.9%
721
0.9%
711
0.9%
701
0.9%

CGD AMBOISE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean37.7961165
Minimum0
Maximum547
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:49.559160image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q325
95-th percentile179.1
Maximum547
Range547
Interquartile range (IQR)25

Descriptive statistics

Standard deviation81.24175484
Coefficient of variation (CV)2.149473606
Kurtosis16.70813099
Mean37.7961165
Median Absolute Deviation (MAD)4
Skewness3.661136034
Sum3893
Variance6600.22273
MonotocityNot monotonic
2021-02-18T22:38:49.655444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
034
31.8%
111
 
10.3%
103
 
2.8%
53
 
2.8%
173
 
2.8%
23
 
2.8%
252
 
1.9%
842
 
1.9%
42
 
1.9%
62
 
1.9%
Other values (36)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
111
 
10.3%
23
 
2.8%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
5471
0.9%
3211
0.9%
2821
0.9%
2591
0.9%
2531
0.9%

CGD CHINON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.70873786
Minimum0
Maximum398
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:38:49.758947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q328
95-th percentile134.9
Maximum398
Range398
Interquartile range (IQR)28

Descriptive statistics

Standard deviation55.12563744
Coefficient of variation (CV)2.063955164
Kurtosis20.60952219
Mean26.70873786
Median Absolute Deviation (MAD)3
Skewness3.915741532
Sum2751
Variance3038.835903
MonotocityNot monotonic
2021-02-18T22:38:49.879261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
029
27.1%
117
15.9%
25
 
4.7%
84
 
3.7%
74
 
3.7%
62
 
1.9%
302
 
1.9%
352
 
1.9%
1162
 
1.9%
232
 
1.9%
Other values (32)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
117
15.9%
25
 
4.7%
32
 
1.9%
41
 
0.9%
ValueCountFrequency (%)
3981
0.9%
1871
0.9%
1801
0.9%
1521
0.9%
1441
0.9%

CGD LOCHES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.10679612
Minimum0
Maximum341
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:50.025921image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q322
95-th percentile150.8
Maximum341
Range341
Interquartile range (IQR)22

Descriptive statistics

Standard deviation52.74799738
Coefficient of variation (CV)2.020469963
Kurtosis13.42618582
Mean26.10679612
Median Absolute Deviation (MAD)2
Skewness3.276676801
Sum2689
Variance2782.351228
MonotocityNot monotonic
2021-02-18T22:38:50.157728image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
036
33.6%
111
 
10.3%
26
 
5.6%
153
 
2.8%
172
 
1.9%
602
 
1.9%
122
 
1.9%
102
 
1.9%
672
 
1.9%
72
 
1.9%
Other values (32)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
111
 
10.3%
26
 
5.6%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
3411
0.9%
1911
0.9%
1841
0.9%
1551
0.9%
1541
0.9%

CGD TOURS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean33.89320388
Minimum0
Maximum518
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:50.267503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q325
95-th percentile159.1
Maximum518
Range518
Interquartile range (IQR)25

Descriptive statistics

Standard deviation73.02791739
Coefficient of variation (CV)2.154647806
Kurtosis20.26807148
Mean33.89320388
Median Absolute Deviation (MAD)5
Skewness3.96001064
Sum3491
Variance5333.076718
MonotocityNot monotonic
2021-02-18T22:38:50.368734image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
45
 
4.7%
55
 
4.7%
194
 
3.7%
33
 
2.8%
143
 
2.8%
73
 
2.8%
242
 
1.9%
1032
 
1.9%
Other values (31)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
21
 
0.9%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
5181
0.9%
2981
0.9%
2461
0.9%
1961
0.9%
1951
0.9%

CGD BOURGOIN JALLIEU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct54
Distinct (%)52.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean65.2038835
Minimum0
Maximum649
Zeros21
Zeros (%)19.6%
Memory size984.0 B
2021-02-18T22:38:50.472399image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q348.5
95-th percentile374
Maximum649
Range649
Interquartile range (IQR)47.5

Descriptive statistics

Standard deviation131.3560764
Coefficient of variation (CV)2.014543757
Kurtosis7.281450546
Mean65.2038835
Median Absolute Deviation (MAD)8
Skewness2.714028518
Sum6716
Variance17254.41881
MonotocityNot monotonic
2021-02-18T22:38:50.577289image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
021
19.6%
212
 
11.2%
17
 
6.5%
35
 
4.7%
93
 
2.8%
152
 
1.9%
62
 
1.9%
3652
 
1.9%
52
 
1.9%
142
 
1.9%
Other values (44)45
42.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
021
19.6%
17
 
6.5%
212
11.2%
35
 
4.7%
41
 
0.9%
ValueCountFrequency (%)
6491
0.9%
6081
0.9%
4951
0.9%
4201
0.9%
3971
0.9%

CGD GRENOBLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean59.60194175
Minimum0
Maximum757
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:38:50.685966image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q344
95-th percentile349.3
Maximum757
Range757
Interquartile range (IQR)43

Descriptive statistics

Standard deviation132.6456536
Coefficient of variation (CV)2.225525707
Kurtosis11.94857862
Mean59.60194175
Median Absolute Deviation (MAD)6
Skewness3.347246611
Sum6139
Variance17594.86941
MonotocityNot monotonic
2021-02-18T22:38:50.790528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
025
23.4%
115
 
14.0%
34
 
3.7%
24
 
3.7%
193
 
2.8%
132
 
1.9%
172
 
1.9%
52
 
1.9%
112
 
1.9%
122
 
1.9%
Other values (38)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
115
14.0%
24
 
3.7%
34
 
3.7%
52
 
1.9%
ValueCountFrequency (%)
7571
0.9%
6241
0.9%
5111
0.9%
4771
0.9%
4631
0.9%

CGD LA MURE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.51456311
Minimum0
Maximum314
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:50.895809image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q320
95-th percentile113.2
Maximum314
Range314
Interquartile range (IQR)20

Descriptive statistics

Standard deviation59.73616241
Coefficient of variation (CV)2.252956693
Kurtosis12.48393323
Mean26.51456311
Median Absolute Deviation (MAD)3
Skewness3.465357792
Sum2731
Variance3568.4091
MonotocityNot monotonic
2021-02-18T22:38:50.989856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
033
30.8%
19
 
8.4%
38
 
7.5%
26
 
5.6%
73
 
2.8%
93
 
2.8%
83
 
2.8%
202
 
1.9%
352
 
1.9%
232
 
1.9%
Other values (28)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
19
 
8.4%
26
 
5.6%
38
 
7.5%
52
 
1.9%
ValueCountFrequency (%)
3141
0.9%
3011
0.9%
2831
0.9%
2151
0.9%
1941
0.9%

CGD LA TOUR DU PIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean41.97087379
Minimum0
Maximum423
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:38:51.096240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q333
95-th percentile206.4
Maximum423
Range423
Interquartile range (IQR)33

Descriptive statistics

Standard deviation86.0416516
Coefficient of variation (CV)2.050032411
Kurtosis8.771950586
Mean41.97087379
Median Absolute Deviation (MAD)5
Skewness2.945820628
Sum4323
Variance7403.16581
MonotocityNot monotonic
2021-02-18T22:38:51.197496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
030
28.0%
19
 
8.4%
27
 
6.5%
54
 
3.7%
222
 
1.9%
282
 
1.9%
272
 
1.9%
302
 
1.9%
92
 
1.9%
902
 
1.9%
Other values (38)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
19
 
8.4%
27
 
6.5%
31
 
0.9%
42
 
1.9%
ValueCountFrequency (%)
4231
0.9%
3931
0.9%
3901
0.9%
3241
0.9%
2741
0.9%

CGD MEYLAN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct54
Distinct (%)52.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean84.2038835
Minimum0
Maximum869
Zeros20
Zeros (%)18.7%
Memory size984.0 B
2021-02-18T22:38:51.326953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median11
Q360
95-th percentile542.3
Maximum869
Range869
Interquartile range (IQR)59

Descriptive statistics

Standard deviation181.2394884
Coefficient of variation (CV)2.152388712
Kurtosis9.624928266
Mean84.2038835
Median Absolute Deviation (MAD)11
Skewness3.111810824
Sum8673
Variance32847.75214
MonotocityNot monotonic
2021-02-18T22:38:51.463391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
020
18.7%
110
 
9.3%
26
 
5.6%
45
 
4.7%
284
 
3.7%
33
 
2.8%
502
 
1.9%
252
 
1.9%
62
 
1.9%
52
 
1.9%
Other values (44)47
43.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
020
18.7%
110
9.3%
26
 
5.6%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
8691
0.9%
8591
0.9%
8281
0.9%
6931
0.9%
5951
0.9%

CGD ST MARCELLIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean38.33980583
Minimum0
Maximum420
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:38:51.594746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q334.5
95-th percentile218.7
Maximum420
Range420
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation74.73161829
Coefficient of variation (CV)1.949191361
Kurtosis9.323595514
Mean38.33980583
Median Absolute Deviation (MAD)6
Skewness2.940067513
Sum3949
Variance5584.814773
MonotocityNot monotonic
2021-02-18T22:38:51.698972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
029
27.1%
27
 
6.5%
66
 
5.6%
15
 
4.7%
73
 
2.8%
163
 
2.8%
33
 
2.8%
43
 
2.8%
142
 
1.9%
172
 
1.9%
Other values (38)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
15
 
4.7%
27
 
6.5%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
4201
0.9%
3071
0.9%
2851
0.9%
2731
0.9%
2531
0.9%

CGD VIENNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct53
Distinct (%)51.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean64.66990291
Minimum0
Maximum720
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:51.803180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q346
95-th percentile354.1
Maximum720
Range720
Interquartile range (IQR)45

Descriptive statistics

Standard deviation131.8942973
Coefficient of variation (CV)2.039500468
Kurtosis9.633605994
Mean64.66990291
Median Absolute Deviation (MAD)9
Skewness3.006918672
Sum6661
Variance17396.10565
MonotocityNot monotonic
2021-02-18T22:38:51.908848image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
024
22.4%
18
 
7.5%
26
 
5.6%
45
 
4.7%
94
 
3.7%
213
 
2.8%
52
 
1.9%
242
 
1.9%
462
 
1.9%
32
 
1.9%
Other values (43)45
42.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
18
 
7.5%
26
 
5.6%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
7201
0.9%
6051
0.9%
5351
0.9%
4711
0.9%
3651
0.9%

CGD DOLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.40776699
Minimum0
Maximum336
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:52.016356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q320
95-th percentile132.6
Maximum336
Range336
Interquartile range (IQR)20

Descriptive statistics

Standard deviation51.4567088
Coefficient of variation (CV)1.948544488
Kurtosis13.08883319
Mean26.40776699
Median Absolute Deviation (MAD)2
Skewness3.162677321
Sum2720
Variance2647.79288
MonotocityNot monotonic
2021-02-18T22:38:52.144100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
037
34.6%
111
 
10.3%
24
 
3.7%
204
 
3.7%
124
 
3.7%
163
 
2.8%
73
 
2.8%
112
 
1.9%
62
 
1.9%
52
 
1.9%
Other values (30)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
111
 
10.3%
24
 
3.7%
41
 
0.9%
52
 
1.9%
ValueCountFrequency (%)
3361
0.9%
1651
0.9%
1641
0.9%
1601
0.9%
1451
0.9%

CGD LONS LE SAUNIER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.04854369
Minimum0
Maximum379
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:52.276681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q321.5
95-th percentile113.3
Maximum379
Range379
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation50.17662502
Coefficient of variation (CV)2.176997632
Kurtosis25.560609
Mean23.04854369
Median Absolute Deviation (MAD)4
Skewness4.385280319
Sum2374
Variance2517.693699
MonotocityNot monotonic
2021-02-18T22:38:52.375484image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
037
34.6%
18
 
7.5%
25
 
4.7%
105
 
4.7%
123
 
2.8%
43
 
2.8%
53
 
2.8%
93
 
2.8%
62
 
1.9%
112
 
1.9%
Other values (30)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
18
 
7.5%
25
 
4.7%
31
 
0.9%
43
 
2.8%
ValueCountFrequency (%)
3791
0.9%
1801
0.9%
1681
0.9%
1261
0.9%
1211
0.9%

CGD ST CLAUDE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.57281553
Minimum0
Maximum199
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:52.479059image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q316
95-th percentile88
Maximum199
Range199
Interquartile range (IQR)16

Descriptive statistics

Standard deviation32.86114636
Coefficient of variation (CV)1.982834256
Kurtosis13.16390429
Mean16.57281553
Median Absolute Deviation (MAD)3
Skewness3.353561029
Sum1707
Variance1079.85494
MonotocityNot monotonic
2021-02-18T22:38:52.578698image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
037
34.6%
27
 
6.5%
17
 
6.5%
44
 
3.7%
104
 
3.7%
73
 
2.8%
92
 
1.9%
212
 
1.9%
62
 
1.9%
492
 
1.9%
Other values (27)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
17
 
6.5%
27
 
6.5%
32
 
1.9%
44
 
3.7%
ValueCountFrequency (%)
1991
0.9%
1671
0.9%
1031
0.9%
1011
0.9%
901
0.9%

CGD DAX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean57.85436893
Minimum0
Maximum820
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:38:52.689473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10
Q340
95-th percentile254.8
Maximum820
Range820
Interquartile range (IQR)40

Descriptive statistics

Standard deviation127.4711354
Coefficient of variation (CV)2.203310445
Kurtosis16.59095616
Mean57.85436893
Median Absolute Deviation (MAD)10
Skewness3.783946871
Sum5959
Variance16248.89035
MonotocityNot monotonic
2021-02-18T22:38:52.790230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
030
28.0%
36
 
5.6%
15
 
4.7%
24
 
3.7%
104
 
3.7%
43
 
2.8%
183
 
2.8%
283
 
2.8%
372
 
1.9%
192
 
1.9%
Other values (39)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
15
 
4.7%
24
 
3.7%
36
 
5.6%
43
 
2.8%
ValueCountFrequency (%)
8201
0.9%
6271
0.9%
4641
0.9%
4221
0.9%
3521
0.9%

CGD MONT DE MARSAN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.21359223
Minimum0
Maximum240
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:52.885433image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q316
95-th percentile93.8
Maximum240
Range240
Interquartile range (IQR)16

Descriptive statistics

Standard deviation35.04720919
Coefficient of variation (CV)2.036019485
Kurtosis16.67638727
Mean17.21359223
Median Absolute Deviation (MAD)2
Skewness3.580990013
Sum1773
Variance1228.306872
MonotocityNot monotonic
2021-02-18T22:38:53.905755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
035
32.7%
19
 
8.4%
28
 
7.5%
46
 
5.6%
94
 
3.7%
233
 
2.8%
82
 
1.9%
162
 
1.9%
222
 
1.9%
62
 
1.9%
Other values (26)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
19
 
8.4%
28
 
7.5%
32
 
1.9%
46
 
5.6%
ValueCountFrequency (%)
2401
0.9%
1321
0.9%
971
0.9%
961
0.9%
951
0.9%

CGD PARENTIS EN BORN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.45631068
Minimum0
Maximum311
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:54.001276image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q318
95-th percentile125
Maximum311
Range311
Interquartile range (IQR)18

Descriptive statistics

Standard deviation52.93276844
Coefficient of variation (CV)2.079357418
Kurtosis11.3166475
Mean25.45631068
Median Absolute Deviation (MAD)4
Skewness3.190661854
Sum2622
Variance2801.877974
MonotocityNot monotonic
2021-02-18T22:38:54.090293image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
036
33.6%
18
 
7.5%
45
 
4.7%
74
 
3.7%
113
 
2.8%
53
 
2.8%
183
 
2.8%
153
 
2.8%
83
 
2.8%
162
 
1.9%
Other values (28)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
18
 
7.5%
22
 
1.9%
31
 
0.9%
45
 
4.7%
ValueCountFrequency (%)
3111
0.9%
2231
0.9%
2141
0.9%
1841
0.9%
1801
0.9%

CGD BLOIS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.30097087
Minimum0
Maximum227
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:54.188649image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q316.5
95-th percentile85.9
Maximum227
Range227
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation33.06821083
Coefficient of variation (CV)1.911350009
Kurtosis16.08119887
Mean17.30097087
Median Absolute Deviation (MAD)3
Skewness3.438942384
Sum1782
Variance1093.506568
MonotocityNot monotonic
2021-02-18T22:38:54.280001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
034
31.8%
110
 
9.3%
26
 
5.6%
35
 
4.7%
63
 
2.8%
103
 
2.8%
83
 
2.8%
163
 
2.8%
42
 
1.9%
112
 
1.9%
Other values (28)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
110
 
9.3%
26
 
5.6%
35
 
4.7%
42
 
1.9%
ValueCountFrequency (%)
2271
0.9%
1101
0.9%
1071
0.9%
961
0.9%
941
0.9%

CGD ROMORANTIN LANTHENAY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean33.25242718
Minimum0
Maximum429
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:54.377876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q326.5
95-th percentile163.5
Maximum429
Range429
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation67.66754348
Coefficient of variation (CV)2.034965541
Kurtosis14.40891082
Mean33.25242718
Median Absolute Deviation (MAD)5
Skewness3.452144639
Sum3425
Variance4578.89644
MonotocityNot monotonic
2021-02-18T22:38:54.489632image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
027
25.2%
113
 
12.1%
55
 
4.7%
65
 
4.7%
23
 
2.8%
33
 
2.8%
113
 
2.8%
243
 
2.8%
173
 
2.8%
272
 
1.9%
Other values (33)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
113
12.1%
23
 
2.8%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
4291
0.9%
3281
0.9%
2201
0.9%
1871
0.9%
1831
0.9%

CGD VENDOME
Real number (ℝ≥0)

MISSING
ZEROS

Distinct30
Distinct (%)29.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean10.39805825
Minimum0
Maximum138
Zeros42
Zeros (%)39.3%
Memory size984.0 B
2021-02-18T22:38:54.607346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q311
95-th percentile47.9
Maximum138
Range138
Interquartile range (IQR)11

Descriptive statistics

Standard deviation21.64795865
Coefficient of variation (CV)2.081923194
Kurtosis15.98683523
Mean10.39805825
Median Absolute Deviation (MAD)1
Skewness3.651571287
Sum1071
Variance468.6341138
MonotocityNot monotonic
2021-02-18T22:38:54.696550image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
042
39.3%
110
 
9.3%
37
 
6.5%
27
 
6.5%
143
 
2.8%
73
 
2.8%
262
 
1.9%
112
 
1.9%
42
 
1.9%
152
 
1.9%
Other values (20)23
21.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
042
39.3%
110
 
9.3%
27
 
6.5%
37
 
6.5%
42
 
1.9%
ValueCountFrequency (%)
1381
0.9%
1111
0.9%
711
0.9%
701
0.9%
571
0.9%

CGD MONTBRISON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean47.27184466
Minimum0
Maximum725
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:38:54.797593image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q335
95-th percentile237.9
Maximum725
Range725
Interquartile range (IQR)34

Descriptive statistics

Standard deviation100.5828304
Coefficient of variation (CV)2.127753446
Kurtosis21.49868343
Mean47.27184466
Median Absolute Deviation (MAD)7
Skewness4.069695472
Sum4869
Variance10116.90577
MonotocityNot monotonic
2021-02-18T22:38:54.898588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
024
22.4%
19
 
8.4%
28
 
7.5%
34
 
3.7%
53
 
2.8%
663
 
2.8%
283
 
2.8%
353
 
2.8%
102
 
1.9%
292
 
1.9%
Other values (35)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
19
 
8.4%
28
 
7.5%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
7251
0.9%
4221
0.9%
2811
0.9%
2751
0.9%
2641
0.9%

CGD ROANNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.13592233
Minimum0
Maximum305
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:38:55.004235image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q319.5
95-th percentile103
Maximum305
Range305
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation43.65193178
Coefficient of variation (CV)1.971995164
Kurtosis17.89387613
Mean22.13592233
Median Absolute Deviation (MAD)5
Skewness3.684089991
Sum2280
Variance1905.491148
MonotocityNot monotonic
2021-02-18T22:38:55.100845image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
029
27.1%
112
 
11.2%
26
 
5.6%
104
 
3.7%
143
 
2.8%
43
 
2.8%
173
 
2.8%
93
 
2.8%
162
 
1.9%
72
 
1.9%
Other values (33)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
112
11.2%
26
 
5.6%
31
 
0.9%
43
 
2.8%
ValueCountFrequency (%)
3051
0.9%
1581
0.9%
1361
0.9%
1321
0.9%
1261
0.9%

CGD ST ETIENNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.03883495
Minimum0
Maximum245
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:55.198309image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q315
95-th percentile96.8
Maximum245
Range245
Interquartile range (IQR)15

Descriptive statistics

Standard deviation42.54845504
Coefficient of variation (CV)2.12329984
Kurtosis12.83304222
Mean20.03883495
Median Absolute Deviation (MAD)2
Skewness3.3612819
Sum2064
Variance1810.371026
MonotocityNot monotonic
2021-02-18T22:38:55.298810image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
035
32.7%
111
 
10.3%
27
 
6.5%
44
 
3.7%
94
 
3.7%
33
 
2.8%
83
 
2.8%
62
 
1.9%
552
 
1.9%
182
 
1.9%
Other values (28)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
111
 
10.3%
27
 
6.5%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
2451
0.9%
2261
0.9%
1451
0.9%
1431
0.9%
1151
0.9%

CGD BRIOUDE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct31
Distinct (%)30.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean15.21359223
Minimum0
Maximum193
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:55.394248image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q311.5
95-th percentile73.8
Maximum193
Range193
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation33.80644169
Coefficient of variation (CV)2.222120928
Kurtosis15.64400474
Mean15.21359223
Median Absolute Deviation (MAD)3
Skewness3.777524148
Sum1567
Variance1142.8755
MonotocityNot monotonic
2021-02-18T22:38:55.491132image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
035
32.7%
19
 
8.4%
27
 
6.5%
35
 
4.7%
114
 
3.7%
213
 
2.8%
93
 
2.8%
83
 
2.8%
53
 
2.8%
43
 
2.8%
Other values (21)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
19
 
8.4%
27
 
6.5%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
1932
1.9%
1351
0.9%
1051
0.9%
1041
0.9%
761
0.9%

CGD LE PUY EN VELAY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean15.62135922
Minimum0
Maximum242
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:55.624911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q315.5
95-th percentile64.7
Maximum242
Range242
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation35.94961521
Coefficient of variation (CV)2.301311601
Kurtosis23.8292968
Mean15.62135922
Median Absolute Deviation (MAD)2
Skewness4.553299738
Sum1609
Variance1292.374833
MonotocityNot monotonic
2021-02-18T22:38:55.759267image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
036
33.6%
113
 
12.1%
75
 
4.7%
104
 
3.7%
24
 
3.7%
172
 
1.9%
112
 
1.9%
122
 
1.9%
142
 
1.9%
82
 
1.9%
Other values (28)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
113
 
12.1%
24
 
3.7%
31
 
0.9%
42
 
1.9%
ValueCountFrequency (%)
2421
0.9%
2121
0.9%
1311
0.9%
701
0.9%
681
0.9%

CGD YSSINGEAUX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.81553398
Minimum0
Maximum337
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:38:55.868628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q323.5
95-th percentile124.7
Maximum337
Range337
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation49.0371503
Coefficient of variation (CV)2.149287864
Kurtosis18.62626494
Mean22.81553398
Median Absolute Deviation (MAD)3
Skewness3.871369033
Sum2350
Variance2404.642109
MonotocityNot monotonic
2021-02-18T22:38:55.964797image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
031
29.0%
112
 
11.2%
25
 
4.7%
34
 
3.7%
93
 
2.8%
123
 
2.8%
43
 
2.8%
73
 
2.8%
103
 
2.8%
113
 
2.8%
Other values (30)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
112
 
11.2%
25
 
4.7%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
3371
0.9%
2221
0.9%
1331
0.9%
1311
0.9%
1281
0.9%

CGD ANCENIS ST GEREON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.04854369
Minimum0
Maximum322
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:38:56.067471image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q323.5
95-th percentile122
Maximum322
Range322
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation55.40039262
Coefficient of variation (CV)2.048183934
Kurtosis11.9753804
Mean27.04854369
Median Absolute Deviation (MAD)3
Skewness3.211961639
Sum2786
Variance3069.203503
MonotocityNot monotonic
2021-02-18T22:38:56.163271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
037
34.6%
18
 
7.5%
37
 
6.5%
65
 
4.7%
24
 
3.7%
562
 
1.9%
102
 
1.9%
1222
 
1.9%
172
 
1.9%
622
 
1.9%
Other values (30)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
18
 
7.5%
24
 
3.7%
37
 
6.5%
42
 
1.9%
ValueCountFrequency (%)
3221
0.9%
2791
0.9%
2151
0.9%
1631
0.9%
1381
0.9%

CGD CHATEAUBRIANT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean38.19417476
Minimum0
Maximum394
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:38:56.269000image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q337.5
95-th percentile205
Maximum394
Range394
Interquartile range (IQR)37.5

Descriptive statistics

Standard deviation75.89234613
Coefficient of variation (CV)1.987013638
Kurtosis9.118642537
Mean38.19417476
Median Absolute Deviation (MAD)5
Skewness2.922361466
Sum3934
Variance5759.648201
MonotocityNot monotonic
2021-02-18T22:38:56.375539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
035
32.7%
18
 
7.5%
25
 
4.7%
54
 
3.7%
232
 
1.9%
262
 
1.9%
692
 
1.9%
142
 
1.9%
32
 
1.9%
202
 
1.9%
Other values (36)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
18
 
7.5%
25
 
4.7%
32
 
1.9%
41
 
0.9%
ValueCountFrequency (%)
3941
0.9%
3671
0.9%
3261
0.9%
2301
0.9%
2251
0.9%

CGD NANTES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean67.54368932
Minimum0
Maximum1326
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:56.485367image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q351.5
95-th percentile327.9
Maximum1326
Range1326
Interquartile range (IQR)51.5

Descriptive statistics

Standard deviation165.2660823
Coefficient of variation (CV)2.446802714
Kurtosis33.55275433
Mean67.54368932
Median Absolute Deviation (MAD)7
Skewness5.065632589
Sum6957
Variance27312.87797
MonotocityNot monotonic
2021-02-18T22:38:56.599582image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
027
25.2%
27
 
6.5%
45
 
4.7%
15
 
4.7%
34
 
3.7%
153
 
2.8%
123
 
2.8%
93
 
2.8%
162
 
1.9%
242
 
1.9%
Other values (40)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
15
 
4.7%
27
 
6.5%
34
 
3.7%
45
 
4.7%
ValueCountFrequency (%)
13261
0.9%
5421
0.9%
5031
0.9%
3971
0.9%
3651
0.9%

CGD PORNIC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean41.17475728
Minimum0
Maximum472
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:56.706604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q329.5
95-th percentile216.9
Maximum472
Range472
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation85.72372715
Coefficient of variation (CV)2.081948573
Kurtosis10.86284771
Mean41.17475728
Median Absolute Deviation (MAD)5
Skewness3.165527508
Sum4241
Variance7348.557396
MonotocityNot monotonic
2021-02-18T22:38:56.810839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
033
30.8%
16
 
5.6%
26
 
5.6%
44
 
3.7%
73
 
2.8%
93
 
2.8%
213
 
2.8%
82
 
1.9%
172
 
1.9%
32
 
1.9%
Other values (38)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
16
 
5.6%
26
 
5.6%
32
 
1.9%
44
 
3.7%
ValueCountFrequency (%)
4721
0.9%
4261
0.9%
3371
0.9%
2871
0.9%
2681
0.9%

CGD REZE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct54
Distinct (%)52.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean101.6893204
Minimum0
Maximum1465
Zeros20
Zeros (%)18.7%
Memory size984.0 B
2021-02-18T22:38:56.915612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q378.5
95-th percentile526.4
Maximum1465
Range1465
Interquartile range (IQR)77.5

Descriptive statistics

Standard deviation218.7856427
Coefficient of variation (CV)2.151510521
Kurtosis16.78259118
Mean101.6893204
Median Absolute Deviation (MAD)9
Skewness3.686777704
Sum10474
Variance47867.15743
MonotocityNot monotonic
2021-02-18T22:38:57.021275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
020
18.7%
17
 
6.5%
27
 
6.5%
35
 
4.7%
94
 
3.7%
43
 
2.8%
83
 
2.8%
72
 
1.9%
352
 
1.9%
542
 
1.9%
Other values (44)48
44.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
020
18.7%
17
 
6.5%
27
 
6.5%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
14651
0.9%
8901
0.9%
8751
0.9%
5521
0.9%
5511
0.9%

CGD ST NAZAIRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean52.33009709
Minimum0
Maximum521
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:38:57.130369image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q354
95-th percentile255.8
Maximum521
Range521
Interquartile range (IQR)54

Descriptive statistics

Standard deviation99.17378175
Coefficient of variation (CV)1.89515761
Kurtosis7.37603556
Mean52.33009709
Median Absolute Deviation (MAD)8
Skewness2.661493039
Sum5390
Variance9835.438987
MonotocityNot monotonic
2021-02-18T22:38:57.239058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
027
25.2%
211
 
10.3%
16
 
5.6%
33
 
2.8%
173
 
2.8%
83
 
2.8%
53
 
2.8%
232
 
1.9%
132
 
1.9%
262
 
1.9%
Other values (39)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
16
 
5.6%
211
10.3%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
5211
0.9%
4221
0.9%
3931
0.9%
3271
0.9%
3141
0.9%

CGD GIEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.74757282
Minimum0
Maximum300
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:57.340225image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q323
95-th percentile95.7
Maximum300
Range300
Interquartile range (IQR)23

Descriptive statistics

Standard deviation46.50146918
Coefficient of variation (CV)2.044238722
Kurtosis15.88474956
Mean22.74757282
Median Absolute Deviation (MAD)4
Skewness3.62134746
Sum2343
Variance2162.386636
MonotocityNot monotonic
2021-02-18T22:38:57.436136image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
034
31.8%
27
 
6.5%
17
 
6.5%
55
 
4.7%
323
 
2.8%
33
 
2.8%
83
 
2.8%
92
 
1.9%
62
 
1.9%
112
 
1.9%
Other values (29)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
17
 
6.5%
27
 
6.5%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
3001
0.9%
2311
0.9%
1651
0.9%
1261
0.9%
1201
0.9%

CGD MONTARGIS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean21.33980583
Minimum0
Maximum269
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:57.535043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q320
95-th percentile85.9
Maximum269
Range269
Interquartile range (IQR)20

Descriptive statistics

Standard deviation42.30805639
Coefficient of variation (CV)1.98258863
Kurtosis13.39430389
Mean21.33980583
Median Absolute Deviation (MAD)2
Skewness3.309765296
Sum2198
Variance1789.971635
MonotocityNot monotonic
2021-02-18T22:38:57.636853image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
033
30.8%
210
 
9.3%
19
 
8.4%
104
 
3.7%
63
 
2.8%
43
 
2.8%
82
 
1.9%
162
 
1.9%
202
 
1.9%
32
 
1.9%
Other values (29)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
19
 
8.4%
210
 
9.3%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
2691
0.9%
1701
0.9%
1651
0.9%
1471
0.9%
1111
0.9%

CGD ORLEANS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean44.91262136
Minimum0
Maximum644
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:38:57.740955image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q338.5
95-th percentile249.6
Maximum644
Range644
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation93.27138422
Coefficient of variation (CV)2.076729912
Kurtosis17.52695581
Mean44.91262136
Median Absolute Deviation (MAD)6
Skewness3.685757327
Sum4626
Variance8699.551114
MonotocityNot monotonic
2021-02-18T22:38:57.846606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
028
26.2%
17
 
6.5%
26
 
5.6%
36
 
5.6%
92
 
1.9%
272
 
1.9%
82
 
1.9%
402
 
1.9%
102
 
1.9%
302
 
1.9%
Other values (40)44
41.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
17
 
6.5%
26
 
5.6%
36
 
5.6%
42
 
1.9%
ValueCountFrequency (%)
6441
0.9%
3421
0.9%
3031
0.9%
2681
0.9%
2621
0.9%

CGD PITHIVIERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.29126214
Minimum0
Maximum378
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:38:57.970769image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q323
95-th percentile132.8
Maximum378
Range378
Interquartile range (IQR)23

Descriptive statistics

Standard deviation57.83743802
Coefficient of variation (CV)2.044356938
Kurtosis15.6092218
Mean28.29126214
Median Absolute Deviation (MAD)6
Skewness3.558979626
Sum2914
Variance3345.169237
MonotocityNot monotonic
2021-02-18T22:38:58.104087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
033
30.8%
17
 
6.5%
25
 
4.7%
95
 
4.7%
64
 
3.7%
233
 
2.8%
43
 
2.8%
72
 
1.9%
212
 
1.9%
132
 
1.9%
Other values (33)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
17
 
6.5%
25
 
4.7%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
3781
0.9%
2741
0.9%
1821
0.9%
1541
0.9%
1501
0.9%

CGD CAHORS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct31
Distinct (%)30.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.95145631
Minimum0
Maximum186
Zeros42
Zeros (%)39.3%
Memory size984.0 B
2021-02-18T22:38:58.223310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q312
95-th percentile72.3
Maximum186
Range186
Interquartile range (IQR)12

Descriptive statistics

Standard deviation27.31241858
Coefficient of variation (CV)2.10882992
Kurtosis16.66354451
Mean12.95145631
Median Absolute Deviation (MAD)2
Skewness3.621095699
Sum1334
Variance745.9682086
MonotocityNot monotonic
2021-02-18T22:38:58.337815image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
042
39.3%
19
 
8.4%
46
 
5.6%
74
 
3.7%
134
 
3.7%
33
 
2.8%
23
 
2.8%
83
 
2.8%
102
 
1.9%
122
 
1.9%
Other values (21)25
23.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
042
39.3%
19
 
8.4%
23
 
2.8%
33
 
2.8%
46
 
5.6%
ValueCountFrequency (%)
1861
0.9%
971
0.9%
871
0.9%
851
0.9%
801
0.9%

CGD FIGEAC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.13592233
Minimum0
Maximum220
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:58.470420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q314.5
95-th percentile79.8
Maximum220
Range220
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation32.32950711
Coefficient of variation (CV)2.003573546
Kurtosis17.24522282
Mean16.13592233
Median Absolute Deviation (MAD)4
Skewness3.705628028
Sum1662
Variance1045.19703
MonotocityNot monotonic
2021-02-18T22:38:58.583294image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
034
31.8%
27
 
6.5%
15
 
4.7%
105
 
4.7%
45
 
4.7%
74
 
3.7%
94
 
3.7%
34
 
3.7%
143
 
2.8%
112
 
1.9%
Other values (26)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
15
 
4.7%
27
 
6.5%
34
 
3.7%
45
 
4.7%
ValueCountFrequency (%)
2201
0.9%
1401
0.9%
1061
0.9%
921
0.9%
881
0.9%

CGD GOURDON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.50485437
Minimum0
Maximum165
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:38:58.681871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310.5
95-th percentile70.3
Maximum165
Range165
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation26.01503102
Coefficient of variation (CV)2.080394561
Kurtosis14.05338736
Mean12.50485437
Median Absolute Deviation (MAD)2
Skewness3.467712551
Sum1288
Variance676.7818389
MonotocityNot monotonic
2021-02-18T22:38:58.771549image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
034
31.8%
116
15.0%
45
 
4.7%
75
 
4.7%
25
 
4.7%
33
 
2.8%
202
 
1.9%
82
 
1.9%
302
 
1.9%
92
 
1.9%
Other values (24)27
25.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
116
15.0%
25
 
4.7%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
1651
0.9%
1061
0.9%
1041
0.9%
831
0.9%
821
0.9%

CGD AGEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.7184466
Minimum0
Maximum287
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:38:58.868953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q322
95-th percentile120.9
Maximum287
Range287
Interquartile range (IQR)22

Descriptive statistics

Standard deviation50.14184145
Coefficient of variation (CV)2.114044073
Kurtosis11.49284544
Mean23.7184466
Median Absolute Deviation (MAD)3
Skewness3.264778614
Sum2443
Variance2514.204264
MonotocityNot monotonic
2021-02-18T22:38:58.964063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
036
33.6%
19
 
8.4%
35
 
4.7%
24
 
3.7%
84
 
3.7%
133
 
2.8%
73
 
2.8%
112
 
1.9%
62
 
1.9%
262
 
1.9%
Other values (27)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
19
 
8.4%
24
 
3.7%
35
 
4.7%
51
 
0.9%
ValueCountFrequency (%)
2871
0.9%
2301
0.9%
2111
0.9%
1741
0.9%
1481
0.9%

CGD MARMANDE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean36.31067961
Minimum0
Maximum413
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:38:59.068656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q330.5
95-th percentile196.2
Maximum413
Range413
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation75.88510783
Coefficient of variation (CV)2.089883986
Kurtosis11.15243457
Mean36.31067961
Median Absolute Deviation (MAD)4
Skewness3.203858865
Sum3740
Variance5758.549591
MonotocityNot monotonic
2021-02-18T22:38:59.168127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
031
29.0%
19
 
8.4%
26
 
5.6%
35
 
4.7%
283
 
2.8%
43
 
2.8%
53
 
2.8%
162
 
1.9%
432
 
1.9%
312
 
1.9%
Other values (35)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
19
 
8.4%
26
 
5.6%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
4131
0.9%
3951
0.9%
2771
0.9%
2681
0.9%
2081
0.9%

CGD VILLENEUVE SUR LOT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.9223301
Minimum0
Maximum223
Zeros42
Zeros (%)39.3%
Memory size984.0 B
2021-02-18T22:38:59.266290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314.5
95-th percentile79.3
Maximum223
Range223
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation36.91741959
Coefficient of variation (CV)2.181580159
Kurtosis13.53048254
Mean16.9223301
Median Absolute Deviation (MAD)2
Skewness3.464082016
Sum1743
Variance1362.895869
MonotocityNot monotonic
2021-02-18T22:38:59.356439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
042
39.3%
18
 
7.5%
27
 
6.5%
44
 
3.7%
84
 
3.7%
552
 
1.9%
92
 
1.9%
62
 
1.9%
162
 
1.9%
142
 
1.9%
Other values (24)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
042
39.3%
18
 
7.5%
27
 
6.5%
31
 
0.9%
44
 
3.7%
ValueCountFrequency (%)
2231
0.9%
1651
0.9%
1631
0.9%
1291
0.9%
881
0.9%

CGD FLORAC TROIS RIVIERES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct22
Distinct (%)21.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean4.54368932
Minimum0
Maximum41
Zeros54
Zeros (%)50.5%
Memory size984.0 B
2021-02-18T22:38:59.445465image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile24.8
Maximum41
Range41
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.62824443
Coefficient of variation (CV)1.898951231
Kurtosis5.244449896
Mean4.54368932
Median Absolute Deviation (MAD)0
Skewness2.371383417
Sum468
Variance74.44660194
MonotocityNot monotonic
2021-02-18T22:38:59.526098image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
054
50.5%
19
 
8.4%
27
 
6.5%
44
 
3.7%
84
 
3.7%
34
 
3.7%
53
 
2.8%
202
 
1.9%
262
 
1.9%
62
 
1.9%
Other values (12)12
 
11.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
054
50.5%
19
 
8.4%
27
 
6.5%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
411
0.9%
371
0.9%
311
0.9%
262
1.9%
251
0.9%

CGD MENDE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.41747573
Minimum0
Maximum173
Zeros40
Zeros (%)37.4%
Memory size984.0 B
2021-02-18T22:38:59.615189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q310.5
95-th percentile67.5
Maximum173
Range173
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation25.32321429
Coefficient of variation (CV)2.039320619
Kurtosis16.60549889
Mean12.41747573
Median Absolute Deviation (MAD)1
Skewness3.581971405
Sum1279
Variance641.2651818
MonotocityNot monotonic
2021-02-18T22:38:59.709896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
040
37.4%
112
 
11.2%
85
 
4.7%
25
 
4.7%
93
 
2.8%
53
 
2.8%
103
 
2.8%
122
 
1.9%
32
 
1.9%
72
 
1.9%
Other values (26)26
24.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
040
37.4%
112
 
11.2%
25
 
4.7%
32
 
1.9%
41
 
0.9%
ValueCountFrequency (%)
1731
0.9%
941
0.9%
761
0.9%
751
0.9%
711
0.9%

CGD ANGERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean48.03883495
Minimum0
Maximum528
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:38:59.814612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median7
Q346
95-th percentile281.5
Maximum528
Range528
Interquartile range (IQR)45.5

Descriptive statistics

Standard deviation92.51390169
Coefficient of variation (CV)1.925814849
Kurtosis8.737233062
Mean48.03883495
Median Absolute Deviation (MAD)7
Skewness2.809215579
Sum4948
Variance8558.822006
MonotocityNot monotonic
2021-02-18T22:38:59.924777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
026
24.3%
112
 
11.2%
26
 
5.6%
43
 
2.8%
73
 
2.8%
172
 
1.9%
112
 
1.9%
92
 
1.9%
32
 
1.9%
132
 
1.9%
Other values (40)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
112
11.2%
26
 
5.6%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
5281
0.9%
3681
0.9%
3171
0.9%
2871
0.9%
2861
0.9%

CGD CHOLET
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean32.7184466
Minimum0
Maximum375
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:00.032180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q327.5
95-th percentile173.2
Maximum375
Range375
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation64.22012046
Coefficient of variation (CV)1.962810803
Kurtosis11.00957974
Mean32.7184466
Median Absolute Deviation (MAD)5
Skewness3.07768237
Sum3370
Variance4124.223872
MonotocityNot monotonic
2021-02-18T22:39:00.137496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
035
32.7%
15
 
4.7%
25
 
4.7%
143
 
2.8%
33
 
2.8%
53
 
2.8%
63
 
2.8%
43
 
2.8%
72
 
1.9%
152
 
1.9%
Other values (38)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
15
 
4.7%
25
 
4.7%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
3751
0.9%
3111
0.9%
2271
0.9%
1831
0.9%
1791
0.9%

CGD SAUMUR
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean30.40776699
Minimum0
Maximum353
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:39:00.245172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q329.5
95-th percentile118.6
Maximum353
Range353
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation58.97763566
Coefficient of variation (CV)1.939558261
Kurtosis12.36315091
Mean30.40776699
Median Absolute Deviation (MAD)4
Skewness3.201531278
Sum3132
Variance3478.361508
MonotocityNot monotonic
2021-02-18T22:39:00.345471image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
029
27.1%
111
 
10.3%
28
 
7.5%
45
 
4.7%
33
 
2.8%
193
 
2.8%
132
 
1.9%
122
 
1.9%
272
 
1.9%
212
 
1.9%
Other values (32)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
111
 
10.3%
28
 
7.5%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
3531
0.9%
3001
0.9%
1971
0.9%
1741
0.9%
1651
0.9%

CGD SEGRE EN ANJOU BLEU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.41747573
Minimum0
Maximum282
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:39:00.450109image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q324.5
95-th percentile134
Maximum282
Range282
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation47.45059852
Coefficient of variation (CV)1.866849369
Kurtosis9.635072646
Mean25.41747573
Median Absolute Deviation (MAD)4
Skewness2.841192333
Sum2618
Variance2251.559299
MonotocityNot monotonic
2021-02-18T22:39:00.546599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
033
30.8%
27
 
6.5%
16
 
5.6%
35
 
4.7%
84
 
3.7%
64
 
3.7%
43
 
2.8%
152
 
1.9%
232
 
1.9%
192
 
1.9%
Other values (34)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
16
 
5.6%
27
 
6.5%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
2821
0.9%
2001
0.9%
1451
0.9%
1391
0.9%
1371
0.9%

CGD AVRANCHES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.33980583
Minimum0
Maximum353
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:00.648153image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q323
95-th percentile102.6
Maximum353
Range353
Interquartile range (IQR)23

Descriptive statistics

Standard deviation53.07570498
Coefficient of variation (CV)2.094558472
Kurtosis17.86809549
Mean25.33980583
Median Absolute Deviation (MAD)4
Skewness3.831301018
Sum2610
Variance2817.030459
MonotocityNot monotonic
2021-02-18T22:39:00.748835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
035
32.7%
19
 
8.4%
24
 
3.7%
63
 
2.8%
43
 
2.8%
183
 
2.8%
122
 
1.9%
992
 
1.9%
152
 
1.9%
52
 
1.9%
Other values (31)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
19
 
8.4%
24
 
3.7%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
3531
0.9%
2661
0.9%
1731
0.9%
1641
0.9%
1271
0.9%

CGD CHERBOURG EN COTENTIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.21359223
Minimum0
Maximum288
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:00.853162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q321
95-th percentile108.8
Maximum288
Range288
Interquartile range (IQR)21

Descriptive statistics

Standard deviation45.27598387
Coefficient of variation (CV)2.038210812
Kurtosis14.23650894
Mean22.21359223
Median Absolute Deviation (MAD)3
Skewness3.473681074
Sum2288
Variance2049.914715
MonotocityNot monotonic
2021-02-18T22:39:00.951171image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
035
32.7%
18
 
7.5%
25
 
4.7%
35
 
4.7%
114
 
3.7%
43
 
2.8%
293
 
2.8%
142
 
1.9%
332
 
1.9%
132
 
1.9%
Other values (31)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
18
 
7.5%
25
 
4.7%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
2881
0.9%
2001
0.9%
1651
0.9%
1481
0.9%
1401
0.9%

CGD COUTANCES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean15.39805825
Minimum0
Maximum204
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:01.054474image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q315
95-th percentile66.6
Maximum204
Range204
Interquartile range (IQR)15

Descriptive statistics

Standard deviation29.78693614
Coefficient of variation (CV)1.934460544
Kurtosis17.15197696
Mean15.39805825
Median Absolute Deviation (MAD)2
Skewness3.632104996
Sum1586
Variance887.2615648
MonotocityNot monotonic
2021-02-18T22:39:01.153912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
034
31.8%
110
 
9.3%
28
 
7.5%
94
 
3.7%
34
 
3.7%
113
 
2.8%
62
 
1.9%
52
 
1.9%
202
 
1.9%
542
 
1.9%
Other values (27)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
110
 
9.3%
28
 
7.5%
34
 
3.7%
52
 
1.9%
ValueCountFrequency (%)
2041
0.9%
1211
0.9%
1121
0.9%
811
0.9%
791
0.9%

CGD ST LO
Real number (ℝ≥0)

MISSING
ZEROS

Distinct31
Distinct (%)30.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean13.96116505
Minimum0
Maximum193
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:39:01.256563image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q314
95-th percentile55.8
Maximum193
Range193
Interquartile range (IQR)14

Descriptive statistics

Standard deviation28.86646821
Coefficient of variation (CV)2.067626026
Kurtosis18.83853021
Mean13.96116505
Median Absolute Deviation (MAD)3
Skewness3.915709274
Sum1438
Variance833.2729869
MonotocityNot monotonic
2021-02-18T22:39:01.351085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
038
35.5%
17
 
6.5%
76
 
5.6%
36
 
5.6%
25
 
4.7%
93
 
2.8%
103
 
2.8%
242
 
1.9%
482
 
1.9%
502
 
1.9%
Other values (21)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
17
 
6.5%
25
 
4.7%
36
 
5.6%
42
 
1.9%
ValueCountFrequency (%)
1931
0.9%
1521
0.9%
931
0.9%
781
0.9%
562
1.9%

CGD CHALONS EN CHAMPAGNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean14.97087379
Minimum0
Maximum188
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:39:01.450708image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q315.5
95-th percentile62.6
Maximum188
Range188
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation29.66362277
Coefficient of variation (CV)1.981422273
Kurtosis14.98788099
Mean14.97087379
Median Absolute Deviation (MAD)3
Skewness3.516897832
Sum1542
Variance879.9305159
MonotocityNot monotonic
2021-02-18T22:39:01.544095image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
038
35.5%
19
 
8.4%
86
 
5.6%
44
 
3.7%
54
 
3.7%
33
 
2.8%
23
 
2.8%
272
 
1.9%
192
 
1.9%
92
 
1.9%
Other values (24)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
19
 
8.4%
23
 
2.8%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
1881
0.9%
1441
0.9%
1231
0.9%
701
0.9%
641
0.9%

CGD EPERNAY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.66019417
Minimum0
Maximum291
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:01.649697image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q321
95-th percentile151.8
Maximum291
Range291
Interquartile range (IQR)21

Descriptive statistics

Standard deviation56.76966765
Coefficient of variation (CV)1.980784474
Kurtosis8.664540067
Mean28.66019417
Median Absolute Deviation (MAD)2
Skewness2.862221066
Sum2952
Variance3222.795165
MonotocityNot monotonic
2021-02-18T22:39:01.748250image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
035
32.7%
29
 
8.4%
18
 
7.5%
213
 
2.8%
32
 
1.9%
132
 
1.9%
392
 
1.9%
1322
 
1.9%
102
 
1.9%
182
 
1.9%
Other values (31)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
18
 
7.5%
29
 
8.4%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
2911
0.9%
2821
0.9%
2121
0.9%
1981
0.9%
1571
0.9%

CGD REIMS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.17475728
Minimum0
Maximum266
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:01.849411image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q320.5
95-th percentile151.8
Maximum266
Range266
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation55.20397598
Coefficient of variation (CV)1.95934167
Kurtosis6.281006127
Mean28.17475728
Median Absolute Deviation (MAD)3
Skewness2.553473059
Sum2902
Variance3047.478964
MonotocityNot monotonic
2021-02-18T22:39:01.953233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
035
32.7%
27
 
6.5%
37
 
6.5%
16
 
5.6%
183
 
2.8%
83
 
2.8%
53
 
2.8%
103
 
2.8%
302
 
1.9%
62
 
1.9%
Other values (31)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
16
 
5.6%
27
 
6.5%
37
 
6.5%
41
 
0.9%
ValueCountFrequency (%)
2661
0.9%
2291
0.9%
2181
0.9%
2001
0.9%
1931
0.9%

CGD VITRY LE FRANCOIS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.38834951
Minimum0
Maximum235
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:02.051621image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q319.5
95-th percentile102.6
Maximum235
Range235
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation43.95412783
Coefficient of variation (CV)1.879317213
Kurtosis7.063594122
Mean23.38834951
Median Absolute Deviation (MAD)3
Skewness2.557921885
Sum2409
Variance1931.965353
MonotocityNot monotonic
2021-02-18T22:39:02.149317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
031
29.0%
110
 
9.3%
210
 
9.3%
36
 
5.6%
104
 
3.7%
83
 
2.8%
972
 
1.9%
112
 
1.9%
912
 
1.9%
42
 
1.9%
Other values (29)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
110
 
9.3%
210
 
9.3%
36
 
5.6%
42
 
1.9%
ValueCountFrequency (%)
2351
0.9%
1861
0.9%
1721
0.9%
1291
0.9%
1181
0.9%

CGD CHAUMONT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct33
Distinct (%)32.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean9.951456311
Minimum0
Maximum109
Zeros47
Zeros (%)43.9%
Memory size984.0 B
2021-02-18T22:39:02.246177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q310
95-th percentile47.7
Maximum109
Range109
Interquartile range (IQR)10

Descriptive statistics

Standard deviation18.72995851
Coefficient of variation (CV)1.882132416
Kurtosis10.28157779
Mean9.951456311
Median Absolute Deviation (MAD)1
Skewness2.939678171
Sum1025
Variance350.8113459
MonotocityNot monotonic
2021-02-18T22:39:02.363911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
047
43.9%
18
 
7.5%
94
 
3.7%
24
 
3.7%
34
 
3.7%
103
 
2.8%
82
 
1.9%
72
 
1.9%
172
 
1.9%
62
 
1.9%
Other values (23)25
23.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
047
43.9%
18
 
7.5%
24
 
3.7%
34
 
3.7%
41
 
0.9%
ValueCountFrequency (%)
1091
0.9%
901
0.9%
621
0.9%
551
0.9%
501
0.9%

CGD LANGRES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct35
Distinct (%)34.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.95145631
Minimum0
Maximum163
Zeros41
Zeros (%)38.3%
Memory size984.0 B
2021-02-18T22:39:02.489479image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q314.5
95-th percentile56
Maximum163
Range163
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation24.89955454
Coefficient of variation (CV)1.922529324
Kurtosis14.10320963
Mean12.95145631
Median Absolute Deviation (MAD)1
Skewness3.299238749
Sum1334
Variance619.9878165
MonotocityNot monotonic
2021-02-18T22:39:02.602497image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
041
38.3%
111
 
10.3%
44
 
3.7%
33
 
2.8%
53
 
2.8%
63
 
2.8%
102
 
1.9%
202
 
1.9%
162
 
1.9%
112
 
1.9%
Other values (25)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
041
38.3%
111
 
10.3%
22
 
1.9%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
1631
0.9%
1061
0.9%
801
0.9%
671
0.9%
651
0.9%

CGD ST DIZIER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct30
Distinct (%)29.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean14.53398058
Minimum0
Maximum166
Zeros44
Zeros (%)41.1%
Memory size984.0 B
2021-02-18T22:39:02.703538image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q310.5
95-th percentile81.8
Maximum166
Range166
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation30.00320752
Coefficient of variation (CV)2.064348948
Kurtosis9.631672509
Mean14.53398058
Median Absolute Deviation (MAD)1
Skewness2.965769455
Sum1497
Variance900.1924615
MonotocityNot monotonic
2021-02-18T22:39:02.793578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
044
41.1%
18
 
7.5%
35
 
4.7%
55
 
4.7%
64
 
3.7%
43
 
2.8%
72
 
1.9%
92
 
1.9%
842
 
1.9%
182
 
1.9%
Other values (20)26
24.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
044
41.1%
18
 
7.5%
22
 
1.9%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
1661
0.9%
1441
0.9%
1021
0.9%
991
0.9%
842
1.9%

CGD CHATEAU GONTIER SUR MAYENNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean31.24271845
Minimum0
Maximum511
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:39:02.893393image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q325
95-th percentile137.7
Maximum511
Range511
Interquartile range (IQR)24

Descriptive statistics

Standard deviation68.56176062
Coefficient of variation (CV)2.194487677
Kurtosis25.30504023
Mean31.24271845
Median Absolute Deviation (MAD)3
Skewness4.417224973
Sum3218
Variance4700.71502
MonotocityNot monotonic
2021-02-18T22:39:03.000647image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
024
22.4%
116
15.0%
26
 
5.6%
36
 
5.6%
204
 
3.7%
73
 
2.8%
182
 
1.9%
342
 
1.9%
132
 
1.9%
282
 
1.9%
Other values (34)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
116
15.0%
26
 
5.6%
36
 
5.6%
42
 
1.9%
ValueCountFrequency (%)
5111
0.9%
3081
0.9%
1831
0.9%
1571
0.9%
1561
0.9%

CGD MAYENNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.53398058
Minimum0
Maximum350
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:03.103626image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q323
95-th percentile124.8
Maximum350
Range350
Interquartile range (IQR)23

Descriptive statistics

Standard deviation54.05603765
Coefficient of variation (CV)2.037238155
Kurtosis15.69994464
Mean26.53398058
Median Absolute Deviation (MAD)3
Skewness3.593219134
Sum2733
Variance2922.055207
MonotocityNot monotonic
2021-02-18T22:39:03.204646image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
031
29.0%
114
13.1%
24
 
3.7%
34
 
3.7%
84
 
3.7%
183
 
2.8%
173
 
2.8%
102
 
1.9%
192
 
1.9%
242
 
1.9%
Other values (32)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
114
13.1%
24
 
3.7%
34
 
3.7%
51
 
0.9%
ValueCountFrequency (%)
3501
0.9%
2621
0.9%
1921
0.9%
1551
0.9%
1331
0.9%

CGD LUNEVILLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean18.02912621
Minimum0
Maximum193
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:39:03.311847image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q318.5
95-th percentile95
Maximum193
Range193
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation35.3149572
Coefficient of variation (CV)1.958772532
Kurtosis10.91766981
Mean18.02912621
Median Absolute Deviation (MAD)2
Skewness3.103882494
Sum1857
Variance1247.146202
MonotocityNot monotonic
2021-02-18T22:39:03.414880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
038
35.5%
110
 
9.3%
45
 
4.7%
24
 
3.7%
33
 
2.8%
613
 
2.8%
102
 
1.9%
232
 
1.9%
252
 
1.9%
82
 
1.9%
Other values (30)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
110
 
9.3%
24
 
3.7%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
1931
0.9%
1881
0.9%
1201
0.9%
1111
0.9%
1091
0.9%

CGD NANCY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean35.08737864
Minimum0
Maximum459
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:04.721351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q329
95-th percentile178.9
Maximum459
Range459
Interquartile range (IQR)29

Descriptive statistics

Standard deviation70.65979066
Coefficient of variation (CV)2.013823585
Kurtosis14.51630033
Mean35.08737864
Median Absolute Deviation (MAD)4
Skewness3.405470043
Sum3614
Variance4992.806016
MonotocityNot monotonic
2021-02-18T22:39:04.824957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
030
28.0%
18
 
7.5%
36
 
5.6%
45
 
4.7%
233
 
2.8%
23
 
2.8%
152
 
1.9%
912
 
1.9%
142
 
1.9%
92
 
1.9%
Other values (36)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
18
 
7.5%
23
 
2.8%
36
 
5.6%
45
 
4.7%
ValueCountFrequency (%)
4591
0.9%
3201
0.9%
2021
0.9%
1891
0.9%
1861
0.9%

CGD TOUL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.7961165
Minimum0
Maximum160
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:39:04.920909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q313
95-th percentile59
Maximum160
Range160
Interquartile range (IQR)13

Descriptive statistics

Standard deviation24.61999794
Coefficient of variation (CV)1.924021083
Kurtosis13.21463444
Mean12.7961165
Median Absolute Deviation (MAD)2
Skewness3.216380695
Sum1318
Variance606.1442985
MonotocityNot monotonic
2021-02-18T22:39:05.016816image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
038
35.5%
112
 
11.2%
25
 
4.7%
45
 
4.7%
313
 
2.8%
93
 
2.8%
103
 
2.8%
62
 
1.9%
82
 
1.9%
592
 
1.9%
Other values (24)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
112
 
11.2%
25
 
4.7%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
1601
0.9%
891
0.9%
841
0.9%
761
0.9%
681
0.9%

CGD VAL DE BRIEY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct35
Distinct (%)34.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean15.76699029
Minimum0
Maximum186
Zeros39
Zeros (%)36.4%
Memory size984.0 B
2021-02-18T22:39:05.118877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q313
95-th percentile78.8
Maximum186
Range186
Interquartile range (IQR)13

Descriptive statistics

Standard deviation32.27461939
Coefficient of variation (CV)2.046974013
Kurtosis11.28956968
Mean15.76699029
Median Absolute Deviation (MAD)3
Skewness3.176162632
Sum1624
Variance1041.651057
MonotocityNot monotonic
2021-02-18T22:39:05.214040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
039
36.4%
18
 
7.5%
46
 
5.6%
55
 
4.7%
23
 
2.8%
73
 
2.8%
33
 
2.8%
83
 
2.8%
632
 
1.9%
92
 
1.9%
Other values (25)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
039
36.4%
18
 
7.5%
23
 
2.8%
33
 
2.8%
46
 
5.6%
ValueCountFrequency (%)
1861
0.9%
1581
0.9%
1141
0.9%
1101
0.9%
871
0.9%

CGD COMMERCY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.39805825
Minimum0
Maximum278
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:39:05.317024image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q324
95-th percentile110
Maximum278
Range278
Interquartile range (IQR)24

Descriptive statistics

Standard deviation46.75999208
Coefficient of variation (CV)1.998456093
Kurtosis12.41942998
Mean23.39805825
Median Absolute Deviation (MAD)3
Skewness3.27607179
Sum2410
Variance2186.496859
MonotocityNot monotonic
2021-02-18T22:39:05.413739image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
029
27.1%
112
 
11.2%
29
 
8.4%
44
 
3.7%
34
 
3.7%
152
 
1.9%
72
 
1.9%
1102
 
1.9%
242
 
1.9%
312
 
1.9%
Other values (33)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
112
11.2%
29
 
8.4%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
2781
0.9%
2351
0.9%
1601
0.9%
1531
0.9%
1161
0.9%

CGD VERDUN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.51456311
Minimum0
Maximum242
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:05.514876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q320.5
95-th percentile107.3
Maximum242
Range242
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation40.01025949
Coefficient of variation (CV)1.950334466
Kurtosis12.32317606
Mean20.51456311
Median Absolute Deviation (MAD)3
Skewness3.21601663
Sum2113
Variance1600.820864
MonotocityNot monotonic
2021-02-18T22:39:05.620170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
034
31.8%
29
 
8.4%
18
 
7.5%
93
 
2.8%
53
 
2.8%
33
 
2.8%
153
 
2.8%
42
 
1.9%
102
 
1.9%
542
 
1.9%
Other values (31)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
18
 
7.5%
29
 
8.4%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
2421
0.9%
1981
0.9%
1211
0.9%
1131
0.9%
1101
0.9%

CGD LORIENT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean59.10679612
Minimum0
Maximum662
Zeros23
Zeros (%)21.5%
Memory size984.0 B
2021-02-18T22:39:05.727505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q351.5
95-th percentile404.6
Maximum662
Range662
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation119.9252147
Coefficient of variation (CV)2.028958132
Kurtosis8.988573723
Mean59.10679612
Median Absolute Deviation (MAD)8
Skewness2.944169378
Sum6088
Variance14382.05711
MonotocityNot monotonic
2021-02-18T22:39:05.834420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
023
21.5%
110
 
9.3%
28
 
7.5%
34
 
3.7%
214
 
3.7%
243
 
2.8%
53
 
2.8%
82
 
1.9%
942
 
1.9%
92
 
1.9%
Other values (40)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
023
21.5%
110
9.3%
28
 
7.5%
34
 
3.7%
53
 
2.8%
ValueCountFrequency (%)
6621
0.9%
4601
0.9%
4371
0.9%
4361
0.9%
4141
0.9%

CGD PLOERMEL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.93203883
Minimum0
Maximum289
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:05.942100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q327
95-th percentile129.1
Maximum289
Range289
Interquartile range (IQR)27

Descriptive statistics

Standard deviation52.78057838
Coefficient of variation (CV)1.889607081
Kurtosis9.522267791
Mean27.93203883
Median Absolute Deviation (MAD)3
Skewness2.870065247
Sum2877
Variance2785.789454
MonotocityNot monotonic
2021-02-18T22:39:06.040602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
035
32.7%
19
 
8.4%
25
 
4.7%
44
 
3.7%
203
 
2.8%
33
 
2.8%
73
 
2.8%
162
 
1.9%
62
 
1.9%
252
 
1.9%
Other values (30)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
19
 
8.4%
25
 
4.7%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
2891
0.9%
2691
0.9%
1891
0.9%
1391
0.9%
1351
0.9%

CGD PONTIVY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.01941748
Minimum0
Maximum294
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:39:06.144552image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q322
95-th percentile111.7
Maximum294
Range294
Interquartile range (IQR)22

Descriptive statistics

Standard deviation49.02719945
Coefficient of variation (CV)1.959565985
Kurtosis12.01217707
Mean25.01941748
Median Absolute Deviation (MAD)4
Skewness3.176648874
Sum2577
Variance2403.666286
MonotocityNot monotonic
2021-02-18T22:39:06.243069image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
029
27.1%
111
 
10.3%
27
 
6.5%
125
 
4.7%
44
 
3.7%
34
 
3.7%
93
 
2.8%
53
 
2.8%
102
 
1.9%
372
 
1.9%
Other values (30)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
111
 
10.3%
27
 
6.5%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
2941
0.9%
2381
0.9%
1861
0.9%
1271
0.9%
1151
0.9%

CGD VANNES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean45.12621359
Minimum0
Maximum554
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:39:06.350513image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q346
95-th percentile254.3
Maximum554
Range554
Interquartile range (IQR)46

Descriptive statistics

Standard deviation89.56164266
Coefficient of variation (CV)1.984692167
Kurtosis11.7323863
Mean45.12621359
Median Absolute Deviation (MAD)6
Skewness3.134355212
Sum4648
Variance8021.287836
MonotocityNot monotonic
2021-02-18T22:39:06.451923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
029
27.1%
112
 
11.2%
64
 
3.7%
94
 
3.7%
33
 
2.8%
253
 
2.8%
462
 
1.9%
162
 
1.9%
22
 
1.9%
262
 
1.9%
Other values (37)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
112
11.2%
22
 
1.9%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
5541
0.9%
3591
0.9%
3001
0.9%
2921
0.9%
2631
0.9%

CGD BOULAY MOSELLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.30097087
Minimum0
Maximum246
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:06.554319image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q318.5
95-th percentile85.3
Maximum246
Range246
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation43.31866304
Coefficient of variation (CV)2.133822235
Kurtosis15.08554042
Mean20.30097087
Median Absolute Deviation (MAD)3
Skewness3.672573113
Sum2091
Variance1876.506568
MonotocityNot monotonic
2021-02-18T22:39:06.657622image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
032
29.9%
112
 
11.2%
37
 
6.5%
44
 
3.7%
53
 
2.8%
752
 
1.9%
142
 
1.9%
252
 
1.9%
82
 
1.9%
122
 
1.9%
Other values (28)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
112
 
11.2%
22
 
1.9%
37
 
6.5%
44
 
3.7%
ValueCountFrequency (%)
2461
0.9%
2411
0.9%
1981
0.9%
1141
0.9%
1031
0.9%

CGD FORBACH
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.95145631
Minimum0
Maximum202
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:06.759801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q317
95-th percentile99.8
Maximum202
Range202
Interquartile range (IQR)17

Descriptive statistics

Standard deviation39.77790761
Coefficient of variation (CV)1.898574831
Kurtosis7.339547175
Mean20.95145631
Median Absolute Deviation (MAD)4
Skewness2.662363378
Sum2158
Variance1582.281934
MonotocityNot monotonic
2021-02-18T22:39:06.861051image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
032
29.9%
18
 
7.5%
27
 
6.5%
85
 
4.7%
53
 
2.8%
33
 
2.8%
43
 
2.8%
123
 
2.8%
113
 
2.8%
72
 
1.9%
Other values (28)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
18
 
7.5%
27
 
6.5%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
2021
0.9%
1911
0.9%
1441
0.9%
1161
0.9%
1141
0.9%

CGD METZ
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean39.0776699
Minimum0
Maximum492
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:39:06.983745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q326.5
95-th percentile185.6
Maximum492
Range492
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation83.93154182
Coefficient of variation (CV)2.147813368
Kurtosis12.22360268
Mean39.0776699
Median Absolute Deviation (MAD)7
Skewness3.320418589
Sum4025
Variance7044.503712
MonotocityNot monotonic
2021-02-18T22:39:07.125772image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
028
26.2%
111
 
10.3%
125
 
4.7%
34
 
3.7%
24
 
3.7%
174
 
3.7%
93
 
2.8%
52
 
1.9%
42
 
1.9%
112
 
1.9%
Other values (35)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
111
 
10.3%
24
 
3.7%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
4921
0.9%
3971
0.9%
3321
0.9%
2941
0.9%
2301
0.9%

CGD SARREBOURG
Real number (ℝ≥0)

MISSING
ZEROS

Distinct35
Distinct (%)34.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.14563107
Minimum0
Maximum190
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:07.247729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q314.5
95-th percentile81.8
Maximum190
Range190
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation32.62845137
Coefficient of variation (CV)2.02088424
Kurtosis14.41910867
Mean16.14563107
Median Absolute Deviation (MAD)3
Skewness3.491789316
Sum1663
Variance1064.615839
MonotocityNot monotonic
2021-02-18T22:39:07.364497image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
035
32.7%
19
 
8.4%
27
 
6.5%
45
 
4.7%
233
 
2.8%
73
 
2.8%
133
 
2.8%
53
 
2.8%
32
 
1.9%
462
 
1.9%
Other values (25)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
19
 
8.4%
27
 
6.5%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
1901
0.9%
1871
0.9%
931
0.9%
901
0.9%
891
0.9%

CGD SARREGUEMINES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct35
Distinct (%)34.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean13.83495146
Minimum0
Maximum177
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:39:07.481409image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q310
95-th percentile67.8
Maximum177
Range177
Interquartile range (IQR)10

Descriptive statistics

Standard deviation27.84941901
Coefficient of variation (CV)2.012975549
Kurtosis13.45064796
Mean13.83495146
Median Absolute Deviation (MAD)3
Skewness3.343949413
Sum1425
Variance775.590139
MonotocityNot monotonic
2021-02-18T22:39:07.621459image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
037
34.6%
17
 
6.5%
36
 
5.6%
55
 
4.7%
25
 
4.7%
64
 
3.7%
94
 
3.7%
83
 
2.8%
103
 
2.8%
72
 
1.9%
Other values (25)27
25.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
17
 
6.5%
25
 
4.7%
36
 
5.6%
42
 
1.9%
ValueCountFrequency (%)
1771
0.9%
1201
0.9%
991
0.9%
811
0.9%
751
0.9%

CGD THIONVILLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean37.57281553
Minimum0
Maximum422
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:39:07.750768image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median6
Q333.5
95-th percentile199
Maximum422
Range422
Interquartile range (IQR)33

Descriptive statistics

Standard deviation76.27653533
Coefficient of variation (CV)2.030099002
Kurtosis9.895813183
Mean37.57281553
Median Absolute Deviation (MAD)6
Skewness3.062278044
Sum3870
Variance5818.109842
MonotocityNot monotonic
2021-02-18T22:39:07.855870image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
026
24.3%
18
 
7.5%
26
 
5.6%
84
 
3.7%
44
 
3.7%
53
 
2.8%
33
 
2.8%
192
 
1.9%
72
 
1.9%
172
 
1.9%
Other values (38)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
18
 
7.5%
26
 
5.6%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
4221
0.9%
3341
0.9%
3151
0.9%
2641
0.9%
2621
0.9%

CGD CHATEAU CHINON VILLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct30
Distinct (%)29.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean10.75728155
Minimum0
Maximum156
Zeros44
Zeros (%)41.1%
Memory size984.0 B
2021-02-18T22:39:07.955869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q310.5
95-th percentile48.7
Maximum156
Range156
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation22.34641087
Coefficient of variation (CV)2.077328808
Kurtosis18.48170416
Mean10.75728155
Median Absolute Deviation (MAD)1
Skewness3.760422031
Sum1108
Variance499.3620788
MonotocityNot monotonic
2021-02-18T22:39:08.050712image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
044
41.1%
19
 
8.4%
25
 
4.7%
34
 
3.7%
54
 
3.7%
73
 
2.8%
143
 
2.8%
83
 
2.8%
112
 
1.9%
702
 
1.9%
Other values (20)24
22.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
044
41.1%
19
 
8.4%
25
 
4.7%
34
 
3.7%
41
 
0.9%
ValueCountFrequency (%)
1561
0.9%
881
0.9%
702
1.9%
551
0.9%
491
0.9%

CGD COSNE COURS SUR LOIRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.3592233
Minimum0
Maximum227
Zeros40
Zeros (%)37.4%
Memory size984.0 B
2021-02-18T22:39:08.158904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q317.5
95-th percentile99.4
Maximum227
Range227
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation36.55934053
Coefficient of variation (CV)1.888471452
Kurtosis11.01495037
Mean19.3592233
Median Absolute Deviation (MAD)3
Skewness2.987860079
Sum1994
Variance1336.58538
MonotocityNot monotonic
2021-02-18T22:39:08.256398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
040
37.4%
17
 
6.5%
83
 
2.8%
93
 
2.8%
23
 
2.8%
133
 
2.8%
43
 
2.8%
63
 
2.8%
33
 
2.8%
122
 
1.9%
Other values (31)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
040
37.4%
17
 
6.5%
23
 
2.8%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
2271
0.9%
1301
0.9%
1261
0.9%
1161
0.9%
1121
0.9%

CGD NEVERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.03883495
Minimum0
Maximum314
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:08.357568image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q326.5
95-th percentile121.9
Maximum314
Range314
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation53.12119372
Coefficient of variation (CV)1.964625836
Kurtosis11.61007638
Mean27.03883495
Median Absolute Deviation (MAD)2
Skewness3.126494271
Sum2785
Variance2821.861222
MonotocityNot monotonic
2021-02-18T22:39:08.459973image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
034
31.8%
110
 
9.3%
28
 
7.5%
33
 
2.8%
83
 
2.8%
62
 
1.9%
162
 
1.9%
52
 
1.9%
492
 
1.9%
112
 
1.9%
Other values (34)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
110
 
9.3%
28
 
7.5%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
3141
0.9%
2641
0.9%
1851
0.9%
1401
0.9%
1391
0.9%

CGD AVESNES SUR HELPE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean34.47572816
Minimum0
Maximum486
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:08.566670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q331.5
95-th percentile154.4
Maximum486
Range486
Interquartile range (IQR)31.5

Descriptive statistics

Standard deviation71.91455233
Coefficient of variation (CV)2.085947308
Kurtosis17.22616116
Mean34.47572816
Median Absolute Deviation (MAD)5
Skewness3.71613964
Sum3551
Variance5171.702836
MonotocityNot monotonic
2021-02-18T22:39:08.677155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
034
31.8%
16
 
5.6%
24
 
3.7%
104
 
3.7%
33
 
2.8%
183
 
2.8%
53
 
2.8%
172
 
1.9%
322
 
1.9%
472
 
1.9%
Other values (36)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
16
 
5.6%
24
 
3.7%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
4861
0.9%
3151
0.9%
2491
0.9%
2141
0.9%
1881
0.9%

CGD CAMBRAI
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean38.52427184
Minimum0
Maximum626
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:08.788227image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q338
95-th percentile173.2
Maximum626
Range626
Interquartile range (IQR)38

Descriptive statistics

Standard deviation83.12981163
Coefficient of variation (CV)2.157855493
Kurtosis25.01097268
Mean38.52427184
Median Absolute Deviation (MAD)4
Skewness4.309830152
Sum3968
Variance6910.565582
MonotocityNot monotonic
2021-02-18T22:39:08.963963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
032
29.9%
111
 
10.3%
25
 
4.7%
33
 
2.8%
123
 
2.8%
172
 
1.9%
492
 
1.9%
112
 
1.9%
602
 
1.9%
62
 
1.9%
Other values (37)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
111
 
10.3%
25
 
4.7%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
6261
0.9%
3121
0.9%
2361
0.9%
2041
0.9%
2021
0.9%

CGD DOUAI
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean44.29126214
Minimum0
Maximum563
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:39:09.106883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q327
95-th percentile213.9
Maximum563
Range563
Interquartile range (IQR)27

Descriptive statistics

Standard deviation94.14138627
Coefficient of variation (CV)2.125506968
Kurtosis12.04669656
Mean44.29126214
Median Absolute Deviation (MAD)5
Skewness3.259084285
Sum4562
Variance8862.600609
MonotocityNot monotonic
2021-02-18T22:39:09.278323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
029
27.1%
19
 
8.4%
94
 
3.7%
194
 
3.7%
34
 
3.7%
24
 
3.7%
43
 
2.8%
133
 
2.8%
53
 
2.8%
212
 
1.9%
Other values (35)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
19
 
8.4%
24
 
3.7%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
5631
0.9%
4131
0.9%
3661
0.9%
3501
0.9%
2301
0.9%

CGD DUNKERQUE HOYMILLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean18.73786408
Minimum0
Maximum272
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:09.408931image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q315
95-th percentile92.7
Maximum272
Range272
Interquartile range (IQR)15

Descriptive statistics

Standard deviation40.6857785
Coefficient of variation (CV)2.171313567
Kurtosis17.34300369
Mean18.73786408
Median Absolute Deviation (MAD)3
Skewness3.759378883
Sum1930
Variance1655.332572
MonotocityNot monotonic
2021-02-18T22:39:09.553056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
035
32.7%
110
 
9.3%
26
 
5.6%
35
 
4.7%
94
 
3.7%
154
 
3.7%
44
 
3.7%
83
 
2.8%
52
 
1.9%
932
 
1.9%
Other values (24)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
110
 
9.3%
26
 
5.6%
35
 
4.7%
44
 
3.7%
ValueCountFrequency (%)
2721
0.9%
1911
0.9%
1281
0.9%
1231
0.9%
932
1.9%

CGD HAZEBROUCK
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.74757282
Minimum0
Maximum211
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:39:09.716172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q316.5
95-th percentile96.9
Maximum211
Range211
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation41.49621255
Coefficient of variation (CV)2.000051424
Kurtosis8.725793472
Mean20.74757282
Median Absolute Deviation (MAD)2
Skewness2.868738419
Sum2137
Variance1721.935656
MonotocityNot monotonic
2021-02-18T22:39:09.862852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
033
30.8%
115
14.0%
26
 
5.6%
85
 
4.7%
93
 
2.8%
43
 
2.8%
192
 
1.9%
142
 
1.9%
242
 
1.9%
112
 
1.9%
Other values (29)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
115
14.0%
26
 
5.6%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
2111
0.9%
1981
0.9%
1841
0.9%
1311
0.9%
1151
0.9%

CGD LILLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean40.03883495
Minimum0
Maximum391
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:10.016150image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q333.5
95-th percentile219.7
Maximum391
Range391
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation77.07787281
Coefficient of variation (CV)1.925077813
Kurtosis7.010754905
Mean40.03883495
Median Absolute Deviation (MAD)5
Skewness2.635296061
Sum4124
Variance5940.998477
MonotocityNot monotonic
2021-02-18T22:39:10.141974image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
031
29.0%
26
 
5.6%
36
 
5.6%
16
 
5.6%
83
 
2.8%
322
 
1.9%
1002
 
1.9%
42
 
1.9%
212
 
1.9%
252
 
1.9%
Other values (38)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
16
 
5.6%
26
 
5.6%
36
 
5.6%
42
 
1.9%
ValueCountFrequency (%)
3911
0.9%
3261
0.9%
3151
0.9%
2691
0.9%
2261
0.9%

CGD VALENCIENNES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct31
Distinct (%)30.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean12.66019417
Minimum0
Maximum144
Zeros41
Zeros (%)38.3%
Memory size984.0 B
2021-02-18T22:39:10.292915image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q311
95-th percentile57.8
Maximum144
Range144
Interquartile range (IQR)11

Descriptive statistics

Standard deviation25.67044283
Coefficient of variation (CV)2.027650009
Kurtosis10.0699584
Mean12.66019417
Median Absolute Deviation (MAD)1
Skewness3.046852658
Sum1304
Variance658.9716353
MonotocityNot monotonic
2021-02-18T22:39:10.441457image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
041
38.3%
112
 
11.2%
36
 
5.6%
105
 
4.7%
53
 
2.8%
43
 
2.8%
143
 
2.8%
72
 
1.9%
92
 
1.9%
172
 
1.9%
Other values (21)24
22.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
041
38.3%
112
 
11.2%
21
 
0.9%
36
 
5.6%
43
 
2.8%
ValueCountFrequency (%)
1441
0.9%
1111
0.9%
1041
0.9%
1021
0.9%
591
0.9%

CGD BEAUVAIS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.81553398
Minimum0
Maximum280
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:39:10.590578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q323.5
95-th percentile114.4
Maximum280
Range280
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation53.63214349
Coefficient of variation (CV)2.000040108
Kurtosis9.575294058
Mean26.81553398
Median Absolute Deviation (MAD)2
Skewness2.968750799
Sum2762
Variance2876.406815
MonotocityNot monotonic
2021-02-18T22:39:10.728318image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
033
30.8%
112
 
11.2%
27
 
6.5%
113
 
2.8%
43
 
2.8%
73
 
2.8%
242
 
1.9%
32
 
1.9%
232
 
1.9%
971
 
0.9%
Other values (35)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
112
 
11.2%
27
 
6.5%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
2801
0.9%
2681
0.9%
2261
0.9%
1801
0.9%
1371
0.9%

CGD CHANTILLY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean41.89320388
Minimum0
Maximum397
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:10.889891image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q326.5
95-th percentile233.6
Maximum397
Range397
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation81.1963141
Coefficient of variation (CV)1.938173894
Kurtosis6.234517559
Mean41.89320388
Median Absolute Deviation (MAD)6
Skewness2.564276927
Sum4315
Variance6592.841424
MonotocityNot monotonic
2021-02-18T22:39:11.068455image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
027
25.2%
29
 
8.4%
17
 
6.5%
36
 
5.6%
63
 
2.8%
242
 
1.9%
192
 
1.9%
202
 
1.9%
122
 
1.9%
212
 
1.9%
Other values (39)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
17
 
6.5%
29
 
8.4%
36
 
5.6%
41
 
0.9%
ValueCountFrequency (%)
3971
0.9%
3231
0.9%
3211
0.9%
2791
0.9%
2731
0.9%

CGD CLERMONT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean37.33009709
Minimum0
Maximum351
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:39:11.232358image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q328
95-th percentile217.8
Maximum351
Range351
Interquartile range (IQR)28

Descriptive statistics

Standard deviation72.03667208
Coefficient of variation (CV)1.929720995
Kurtosis6.011360564
Mean37.33009709
Median Absolute Deviation (MAD)5
Skewness2.530276353
Sum3845
Variance5189.282125
MonotocityNot monotonic
2021-02-18T22:39:11.382947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
029
27.1%
110
 
9.3%
28
 
7.5%
84
 
3.7%
144
 
3.7%
213
 
2.8%
172
 
1.9%
42
 
1.9%
222
 
1.9%
32
 
1.9%
Other values (33)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
110
 
9.3%
28
 
7.5%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
3511
0.9%
2991
0.9%
2681
0.9%
2331
0.9%
2311
0.9%

CGD COMPIEGNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean44.45631068
Minimum0
Maximum408
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:11.526802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q339
95-th percentile232.7
Maximum408
Range408
Interquartile range (IQR)39

Descriptive statistics

Standard deviation84.81257037
Coefficient of variation (CV)1.907773476
Kurtosis8.059154687
Mean44.45631068
Median Absolute Deviation (MAD)8
Skewness2.7999843
Sum4579
Variance7193.172092
MonotocityNot monotonic
2021-02-18T22:39:11.660725image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
027
25.2%
29
 
8.4%
16
 
5.6%
223
 
2.8%
83
 
2.8%
143
 
2.8%
32
 
1.9%
242
 
1.9%
192
 
1.9%
392
 
1.9%
Other values (39)44
41.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
16
 
5.6%
29
 
8.4%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
4081
0.9%
3981
0.9%
3901
0.9%
2691
0.9%
2661
0.9%

CGD MERU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean46.17475728
Minimum0
Maximum446
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:39:11.818880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median9
Q343.5
95-th percentile217.9
Maximum446
Range446
Interquartile range (IQR)43

Descriptive statistics

Standard deviation85.24813001
Coefficient of variation (CV)1.846206348
Kurtosis7.405622953
Mean46.17475728
Median Absolute Deviation (MAD)9
Skewness2.648268135
Sum4756
Variance7267.24367
MonotocityNot monotonic
2021-02-18T22:39:11.958889image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
026
24.3%
17
 
6.5%
55
 
4.7%
95
 
4.7%
25
 
4.7%
123
 
2.8%
33
 
2.8%
43
 
2.8%
522
 
1.9%
252
 
1.9%
Other values (38)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
17
 
6.5%
25
 
4.7%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
4461
0.9%
3941
0.9%
2981
0.9%
2911
0.9%
2471
0.9%

CGD SENLIS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean43.51456311
Minimum0
Maximum477
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:39:12.099148image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q331
95-th percentile234.7
Maximum477
Range477
Interquartile range (IQR)30

Descriptive statistics

Standard deviation84.85245142
Coefficient of variation (CV)1.949978245
Kurtosis8.655969717
Mean43.51456311
Median Absolute Deviation (MAD)8
Skewness2.828551661
Sum4482
Variance7199.938511
MonotocityNot monotonic
2021-02-18T22:39:12.244905image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
024
22.4%
110
 
9.3%
26
 
5.6%
44
 
3.7%
34
 
3.7%
53
 
2.8%
83
 
2.8%
202
 
1.9%
92
 
1.9%
112
 
1.9%
Other values (37)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
110
9.3%
26
 
5.6%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
4771
0.9%
3451
0.9%
3171
0.9%
2671
0.9%
2661
0.9%

CGD ALENCON ARGENTAN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.49514563
Minimum0
Maximum266
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:39:12.365092image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q325
95-th percentile106.8
Maximum266
Range266
Interquartile range (IQR)25

Descriptive statistics

Standard deviation45.57172192
Coefficient of variation (CV)1.939622875
Kurtosis11.43682209
Mean23.49514563
Median Absolute Deviation (MAD)4
Skewness3.1647351
Sum2420
Variance2076.781839
MonotocityNot monotonic
2021-02-18T22:39:12.472432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
036
33.6%
16
 
5.6%
55
 
4.7%
45
 
4.7%
103
 
2.8%
163
 
2.8%
23
 
2.8%
32
 
1.9%
372
 
1.9%
122
 
1.9%
Other values (33)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
16
 
5.6%
23
 
2.8%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
2661
0.9%
2121
0.9%
1971
0.9%
1271
0.9%
1231
0.9%

CGD DOMFRONT EN POIRAIE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean18.66990291
Minimum0
Maximum205
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:12.578436image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q316.5
95-th percentile101
Maximum205
Range205
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation36.14252515
Coefficient of variation (CV)1.935871082
Kurtosis9.97096904
Mean18.66990291
Median Absolute Deviation (MAD)2
Skewness2.998357165
Sum1923
Variance1306.282125
MonotocityNot monotonic
2021-02-18T22:39:12.675149image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
031
29.0%
116
15.0%
25
 
4.7%
154
 
3.7%
44
 
3.7%
453
 
2.8%
63
 
2.8%
73
 
2.8%
502
 
1.9%
82
 
1.9%
Other values (27)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
116
15.0%
25
 
4.7%
44
 
3.7%
52
 
1.9%
ValueCountFrequency (%)
2051
0.9%
1671
0.9%
1311
0.9%
1191
0.9%
1171
0.9%

CGD MORTAGNE AU PERCHE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.91262136
Minimum0
Maximum288
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:12.776200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q325
95-th percentile128.4
Maximum288
Range288
Interquartile range (IQR)25

Descriptive statistics

Standard deviation49.63674058
Coefficient of variation (CV)1.915543005
Kurtosis10.35763984
Mean25.91262136
Median Absolute Deviation (MAD)4
Skewness3.000597778
Sum2669
Variance2463.806016
MonotocityNot monotonic
2021-02-18T22:39:12.878589image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
031
29.0%
111
 
10.3%
45
 
4.7%
64
 
3.7%
134
 
3.7%
103
 
2.8%
23
 
2.8%
53
 
2.8%
252
 
1.9%
142
 
1.9%
Other values (32)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
111
 
10.3%
23
 
2.8%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
2881
0.9%
2341
0.9%
1701
0.9%
1611
0.9%
1371
0.9%

CGD ARRAS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean36.04854369
Minimum0
Maximum365
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:12.987282image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q330.5
95-th percentile180
Maximum365
Range365
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation73.47833863
Coefficient of variation (CV)2.038316423
Kurtosis8.878508537
Mean36.04854369
Median Absolute Deviation (MAD)4
Skewness2.945161981
Sum3713
Variance5399.066248
MonotocityNot monotonic
2021-02-18T22:39:13.093728image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
032
29.9%
17
 
6.5%
26
 
5.6%
36
 
5.6%
83
 
2.8%
372
 
1.9%
182
 
1.9%
1272
 
1.9%
42
 
1.9%
252
 
1.9%
Other values (35)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
17
 
6.5%
26
 
5.6%
36
 
5.6%
42
 
1.9%
ValueCountFrequency (%)
3651
0.9%
3401
0.9%
3171
0.9%
3041
0.9%
1991
0.9%

CGD BETHUNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.61165049
Minimum0
Maximum225
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:13.206295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q317
95-th percentile100
Maximum225
Range225
Interquartile range (IQR)17

Descriptive statistics

Standard deviation41.19400133
Coefficient of variation (CV)2.100486206
Kurtosis10.87546313
Mean19.61165049
Median Absolute Deviation (MAD)2
Skewness3.168120692
Sum2020
Variance1696.945745
MonotocityNot monotonic
2021-02-18T22:39:13.329384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
035
32.7%
210
 
9.3%
110
 
9.3%
66
 
5.6%
174
 
3.7%
113
 
2.8%
32
 
1.9%
42
 
1.9%
252
 
1.9%
102
 
1.9%
Other values (26)27
25.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
110
 
9.3%
210
 
9.3%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
2251
0.9%
2041
0.9%
1781
0.9%
1211
0.9%
1021
0.9%

CGD CALAIS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.58252427
Minimum0
Maximum288
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:39:13.455040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q317
95-th percentile124
Maximum288
Range288
Interquartile range (IQR)17

Descriptive statistics

Standard deviation49.14574648
Coefficient of variation (CV)2.083990073
Kurtosis12.16751579
Mean23.58252427
Median Absolute Deviation (MAD)3
Skewness3.258513553
Sum2429
Variance2415.304397
MonotocityNot monotonic
2021-02-18T22:39:13.574908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
036
33.6%
27
 
6.5%
15
 
4.7%
34
 
3.7%
103
 
2.8%
113
 
2.8%
53
 
2.8%
73
 
2.8%
452
 
1.9%
362
 
1.9%
Other values (28)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
15
 
4.7%
27
 
6.5%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
2881
0.9%
2521
0.9%
1501
0.9%
1381
0.9%
1311
0.9%

CGD ECUIRES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.59223301
Minimum0
Maximum278
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:13.677650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q325
95-th percentile137
Maximum278
Range278
Interquartile range (IQR)25

Descriptive statistics

Standard deviation50.68693549
Coefficient of variation (CV)1.906080451
Kurtosis9.301859697
Mean26.59223301
Median Absolute Deviation (MAD)4
Skewness2.87453209
Sum2739
Variance2569.165429
MonotocityNot monotonic
2021-02-18T22:39:13.778352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
035
32.7%
18
 
7.5%
25
 
4.7%
45
 
4.7%
33
 
2.8%
212
 
1.9%
92
 
1.9%
142
 
1.9%
292
 
1.9%
152
 
1.9%
Other values (34)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
18
 
7.5%
25
 
4.7%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
2781
0.9%
2511
0.9%
1791
0.9%
1461
0.9%
1391
0.9%

CGD ST OMER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.60194175
Minimum0
Maximum340
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:13.884308image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q322.5
95-th percentile138.3
Maximum340
Range340
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation57.74119741
Coefficient of variation (CV)2.091925196
Kurtosis15.41702158
Mean27.60194175
Median Absolute Deviation (MAD)4
Skewness3.589738005
Sum2843
Variance3334.045879
MonotocityNot monotonic
2021-02-18T22:39:13.987435image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
25
 
4.7%
34
 
3.7%
44
 
3.7%
134
 
3.7%
163
 
2.8%
82
 
1.9%
152
 
1.9%
102
 
1.9%
Other values (33)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
25
 
4.7%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
3401
0.9%
3371
0.9%
1521
0.9%
1441
0.9%
1402
1.9%

CGD ST POL SUR TERNOISE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.24271845
Minimum0
Maximum238
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:39:14.091729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q319
95-th percentile96.8
Maximum238
Range238
Interquartile range (IQR)19

Descriptive statistics

Standard deviation40.01310227
Coefficient of variation (CV)1.976666443
Kurtosis11.11294734
Mean20.24271845
Median Absolute Deviation (MAD)3
Skewness3.105670189
Sum2085
Variance1601.048353
MonotocityNot monotonic
2021-02-18T22:39:14.191477image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
037
34.6%
18
 
7.5%
26
 
5.6%
35
 
4.7%
54
 
3.7%
153
 
2.8%
193
 
2.8%
132
 
1.9%
112
 
1.9%
82
 
1.9%
Other values (29)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
18
 
7.5%
26
 
5.6%
35
 
4.7%
54
 
3.7%
ValueCountFrequency (%)
2381
0.9%
1751
0.9%
1571
0.9%
1331
0.9%
1011
0.9%

CGD AMBERT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct25
Distinct (%)24.3%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean7.184466019
Minimum0
Maximum98
Zeros47
Zeros (%)43.9%
Memory size984.0 B
2021-02-18T22:39:14.286469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q37.5
95-th percentile35.8
Maximum98
Range98
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation14.21249628
Coefficient of variation (CV)1.978225833
Kurtosis16.94358905
Mean7.184466019
Median Absolute Deviation (MAD)1
Skewness3.55189938
Sum740
Variance201.9950504
MonotocityNot monotonic
2021-02-18T22:39:14.378391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
047
43.9%
19
 
8.4%
58
 
7.5%
26
 
5.6%
94
 
3.7%
33
 
2.8%
202
 
1.9%
372
 
1.9%
272
 
1.9%
42
 
1.9%
Other values (15)18
 
16.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
047
43.9%
19
 
8.4%
26
 
5.6%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
981
0.9%
561
0.9%
401
0.9%
372
1.9%
361
0.9%

CGD CLERMONT FERRAND
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.15533981
Minimum0
Maximum401
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:14.478678image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q321
95-th percentile151.6
Maximum401
Range401
Interquartile range (IQR)21

Descriptive statistics

Standard deviation59.84043444
Coefficient of variation (CV)2.125367154
Kurtosis16.5916882
Mean28.15533981
Median Absolute Deviation (MAD)4
Skewness3.655044046
Sum2900
Variance3580.877594
MonotocityNot monotonic
2021-02-18T22:39:14.587034image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
034
31.8%
110
 
9.3%
114
 
3.7%
24
 
3.7%
33
 
2.8%
133
 
2.8%
163
 
2.8%
43
 
2.8%
92
 
1.9%
52
 
1.9%
Other values (33)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
110
 
9.3%
24
 
3.7%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
4011
0.9%
2531
0.9%
2121
0.9%
1721
0.9%
1631
0.9%

CGD ISSOIRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.02912621
Minimum0
Maximum321
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:14.697907image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q321.5
95-th percentile113.4
Maximum321
Range321
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation46.00009725
Coefficient of variation (CV)1.997474712
Kurtosis18.12491508
Mean23.02912621
Median Absolute Deviation (MAD)3
Skewness3.706676999
Sum2372
Variance2116.008947
MonotocityNot monotonic
2021-02-18T22:39:14.797636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
034
31.8%
111
 
10.3%
35
 
4.7%
104
 
3.7%
23
 
2.8%
53
 
2.8%
312
 
1.9%
622
 
1.9%
132
 
1.9%
152
 
1.9%
Other values (30)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
111
 
10.3%
23
 
2.8%
35
 
4.7%
53
 
2.8%
ValueCountFrequency (%)
3211
0.9%
1651
0.9%
1641
0.9%
1411
0.9%
1261
0.9%

CGD RIOM
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.75728155
Minimum0
Maximum343
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:14.905563image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q325
95-th percentile120.5
Maximum343
Range343
Interquartile range (IQR)25

Descriptive statistics

Standard deviation59.84595683
Coefficient of variation (CV)2.081071423
Kurtosis14.26686266
Mean28.75728155
Median Absolute Deviation (MAD)4
Skewness3.497419311
Sum2962
Variance3581.538549
MonotocityNot monotonic
2021-02-18T22:39:15.011479image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
031
29.0%
113
 
12.1%
94
 
3.7%
24
 
3.7%
53
 
2.8%
33
 
2.8%
193
 
2.8%
83
 
2.8%
62
 
1.9%
72
 
1.9%
Other values (35)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
113
12.1%
24
 
3.7%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
3431
0.9%
3411
0.9%
2121
0.9%
1691
0.9%
1661
0.9%

CGD THIERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.52427184
Minimum0
Maximum250
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:39:15.117439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q315.5
95-th percentile86.9
Maximum250
Range250
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation36.78897018
Coefficient of variation (CV)2.099315196
Kurtosis17.51785502
Mean17.52427184
Median Absolute Deviation (MAD)2
Skewness3.72943692
Sum1805
Variance1353.428327
MonotocityNot monotonic
2021-02-18T22:39:15.222034image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
037
34.6%
112
 
11.2%
23
 
2.8%
73
 
2.8%
133
 
2.8%
43
 
2.8%
62
 
1.9%
102
 
1.9%
52
 
1.9%
162
 
1.9%
Other values (28)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
112
 
11.2%
23
 
2.8%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
2501
0.9%
1661
0.9%
1031
0.9%
971
0.9%
951
0.9%

CGD BAYONNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.73786408
Minimum0
Maximum320
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:15.322428image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q321
95-th percentile97.8
Maximum320
Range320
Interquartile range (IQR)21

Descriptive statistics

Standard deviation42.70095769
Coefficient of variation (CV)2.059081761
Kurtosis24.111612
Mean20.73786408
Median Absolute Deviation (MAD)3
Skewness4.216499203
Sum2136
Variance1823.371788
MonotocityNot monotonic
2021-02-18T22:39:15.419605image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
034
31.8%
29
 
8.4%
17
 
6.5%
395
 
4.7%
34
 
3.7%
143
 
2.8%
93
 
2.8%
112
 
1.9%
372
 
1.9%
212
 
1.9%
Other values (27)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
17
 
6.5%
29
 
8.4%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
3201
0.9%
1551
0.9%
1191
0.9%
1161
0.9%
1131
0.9%

CGD OLORON STE MARIE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct32
Distinct (%)31.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean13.0776699
Minimum0
Maximum196
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:15.521938image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q312
95-th percentile68.8
Maximum196
Range196
Interquartile range (IQR)12

Descriptive statistics

Standard deviation28.13263032
Coefficient of variation (CV)2.151195934
Kurtosis19.26987522
Mean13.0776699
Median Absolute Deviation (MAD)2
Skewness3.92015705
Sum1347
Variance791.4448886
MonotocityNot monotonic
2021-02-18T22:39:15.620444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
034
31.8%
117
15.9%
27
 
6.5%
104
 
3.7%
33
 
2.8%
123
 
2.8%
133
 
2.8%
112
 
1.9%
522
 
1.9%
162
 
1.9%
Other values (22)26
24.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
117
15.9%
27
 
6.5%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
1961
0.9%
1201
0.9%
921
0.9%
781
0.9%
761
0.9%

CGD ORTHEZ
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.90291262
Minimum0
Maximum280
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:39:15.723448image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q316.5
95-th percentile92.8
Maximum280
Range280
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation41.07131878
Coefficient of variation (CV)2.063583334
Kurtosis17.74162007
Mean19.90291262
Median Absolute Deviation (MAD)3
Skewness3.726183926
Sum2050
Variance1686.853227
MonotocityNot monotonic
2021-02-18T22:39:15.817403image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
038
35.5%
18
 
7.5%
64
 
3.7%
24
 
3.7%
34
 
3.7%
423
 
2.8%
323
 
2.8%
162
 
1.9%
142
 
1.9%
92
 
1.9%
Other values (28)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
18
 
7.5%
24
 
3.7%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
2801
0.9%
1891
0.9%
1151
0.9%
1111
0.9%
1021
0.9%

CGD PAU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.33009709
Minimum0
Maximum381
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:39:15.920108image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q317.5
95-th percentile128.6
Maximum381
Range381
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation53.25657252
Coefficient of variation (CV)2.282741144
Kurtosis21.29071038
Mean23.33009709
Median Absolute Deviation (MAD)3
Skewness4.106305615
Sum2403
Variance2836.262517
MonotocityNot monotonic
2021-02-18T22:39:16.023216image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
036
33.6%
110
 
9.3%
75
 
4.7%
44
 
3.7%
24
 
3.7%
53
 
2.8%
133
 
2.8%
32
 
1.9%
152
 
1.9%
292
 
1.9%
Other values (26)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
110
 
9.3%
24
 
3.7%
32
 
1.9%
44
 
3.7%
ValueCountFrequency (%)
3811
0.9%
2091
0.9%
1681
0.9%
1601
0.9%
1401
0.9%

CGD ARGELES GAZOST
Real number (ℝ≥0)

MISSING
ZEROS

Distinct24
Distinct (%)23.3%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean6.262135922
Minimum0
Maximum94
Zeros43
Zeros (%)40.2%
Memory size984.0 B
2021-02-18T22:39:16.124450image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34.5
95-th percentile37.9
Maximum94
Range94
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation13.69840492
Coefficient of variation (CV)2.18749722
Kurtosis17.73108418
Mean6.262135922
Median Absolute Deviation (MAD)1
Skewness3.772309154
Sum645
Variance187.6462974
MonotocityNot monotonic
2021-02-18T22:39:16.212150image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
043
40.2%
312
 
11.2%
111
 
10.3%
28
 
7.5%
54
 
3.7%
43
 
2.8%
72
 
1.9%
272
 
1.9%
432
 
1.9%
122
 
1.9%
Other values (14)14
 
13.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
043
40.2%
111
 
10.3%
28
 
7.5%
312
 
11.2%
43
 
2.8%
ValueCountFrequency (%)
941
0.9%
511
0.9%
432
1.9%
421
0.9%
391
0.9%

CGD BAGNERES DE BIGORRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean15.88349515
Minimum0
Maximum203
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:39:16.308469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q315.5
95-th percentile82.8
Maximum203
Range203
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation32.57218258
Coefficient of variation (CV)2.050693646
Kurtosis13.43181159
Mean15.88349515
Median Absolute Deviation (MAD)2
Skewness3.374359193
Sum1636
Variance1060.947078
MonotocityNot monotonic
2021-02-18T22:39:16.411858image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
037
34.6%
114
 
13.1%
24
 
3.7%
73
 
2.8%
33
 
2.8%
153
 
2.8%
172
 
1.9%
42
 
1.9%
102
 
1.9%
162
 
1.9%
Other values (28)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
114
 
13.1%
24
 
3.7%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
2031
0.9%
1501
0.9%
1211
0.9%
911
0.9%
901
0.9%

CGD TARBES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.21359223
Minimum0
Maximum252
Zeros40
Zeros (%)37.4%
Memory size984.0 B
2021-02-18T22:39:16.516677image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q316.5
95-th percentile101.4
Maximum252
Range252
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation37.40442736
Coefficient of variation (CV)2.172958837
Kurtosis17.06895822
Mean17.21359223
Median Absolute Deviation (MAD)3
Skewness3.744308654
Sum1773
Variance1399.091186
MonotocityNot monotonic
2021-02-18T22:39:16.620749image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
040
37.4%
18
 
7.5%
56
 
5.6%
134
 
3.7%
64
 
3.7%
44
 
3.7%
213
 
2.8%
23
 
2.8%
72
 
1.9%
172
 
1.9%
Other values (27)27
25.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
040
37.4%
18
 
7.5%
23
 
2.8%
31
 
0.9%
44
 
3.7%
ValueCountFrequency (%)
2521
0.9%
1551
0.9%
1211
0.9%
1161
0.9%
1131
0.9%

CGD CERET
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean36.29126214
Minimum0
Maximum390
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:39:16.726764image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median8
Q331
95-th percentile156.9
Maximum390
Range390
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation74.40939102
Coefficient of variation (CV)2.050339025
Kurtosis11.19937592
Mean36.29126214
Median Absolute Deviation (MAD)8
Skewness3.284790328
Sum3738
Variance5536.757472
MonotocityNot monotonic
2021-02-18T22:39:16.833230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
026
24.3%
110
 
9.3%
47
 
6.5%
194
 
3.7%
264
 
3.7%
83
 
2.8%
73
 
2.8%
133
 
2.8%
93
 
2.8%
32
 
1.9%
Other values (32)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
110
 
9.3%
22
 
1.9%
32
 
1.9%
47
 
6.5%
ValueCountFrequency (%)
3901
0.9%
3581
0.9%
3341
0.9%
3131
0.9%
2321
0.9%

CGD PERPIGNAN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean57.59223301
Minimum0
Maximum772
Zeros23
Zeros (%)21.5%
Memory size984.0 B
2021-02-18T22:39:16.948629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q346.5
95-th percentile309
Maximum772
Range772
Interquartile range (IQR)45.5

Descriptive statistics

Standard deviation125.791723
Coefficient of variation (CV)2.184178603
Kurtosis14.82850135
Mean57.59223301
Median Absolute Deviation (MAD)9
Skewness3.64047729
Sum5932
Variance15823.55759
MonotocityNot monotonic
2021-02-18T22:39:17.061048image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
023
21.5%
19
 
8.4%
35
 
4.7%
24
 
3.7%
73
 
2.8%
63
 
2.8%
183
 
2.8%
353
 
2.8%
682
 
1.9%
142
 
1.9%
Other values (40)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
023
21.5%
19
 
8.4%
24
 
3.7%
35
 
4.7%
41
 
0.9%
ValueCountFrequency (%)
7721
0.9%
6341
0.9%
4411
0.9%
4371
0.9%
3801
0.9%

CGD PRADES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean18.19417476
Minimum0
Maximum177
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:17.173812image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q316.5
95-th percentile106
Maximum177
Range177
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation34.85236601
Coefficient of variation (CV)1.915578281
Kurtosis8.499823755
Mean18.19417476
Median Absolute Deviation (MAD)4
Skewness2.895488709
Sum1874
Variance1214.687417
MonotocityNot monotonic
2021-02-18T22:39:17.273300image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
031
29.0%
111
 
10.3%
26
 
5.6%
64
 
3.7%
243
 
2.8%
43
 
2.8%
53
 
2.8%
153
 
2.8%
102
 
1.9%
202
 
1.9%
Other values (29)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
111
 
10.3%
26
 
5.6%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
1771
0.9%
1571
0.9%
1501
0.9%
1271
0.9%
1161
0.9%

CGD RIVESALTES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean44.06796117
Minimum0
Maximum533
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:39:17.380523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median6
Q334.5
95-th percentile220.1
Maximum533
Range533
Interquartile range (IQR)34

Descriptive statistics

Standard deviation91.67977754
Coefficient of variation (CV)2.080417953
Kurtosis11.16772924
Mean44.06796117
Median Absolute Deviation (MAD)6
Skewness3.172083019
Sum4539
Variance8405.181611
MonotocityNot monotonic
2021-02-18T22:39:17.494158image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
026
24.3%
19
 
8.4%
27
 
6.5%
34
 
3.7%
53
 
2.8%
83
 
2.8%
172
 
1.9%
362
 
1.9%
192
 
1.9%
182
 
1.9%
Other values (38)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
19
 
8.4%
27
 
6.5%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
5331
0.9%
4161
0.9%
3432
1.9%
2461
0.9%
2221
0.9%

CGD HAGUENAU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.99029126
Minimum0
Maximum400
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:17.602209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q323
95-th percentile167.8
Maximum400
Range400
Interquartile range (IQR)23

Descriptive statistics

Standard deviation62.00118518
Coefficient of variation (CV)2.138687901
Kurtosis15.66066792
Mean28.99029126
Median Absolute Deviation (MAD)5
Skewness3.652000377
Sum2986
Variance3844.146964
MonotocityNot monotonic
2021-02-18T22:39:17.708793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
030
28.0%
19
 
8.4%
217
 
6.5%
25
 
4.7%
55
 
4.7%
143
 
2.8%
43
 
2.8%
33
 
2.8%
232
 
1.9%
492
 
1.9%
Other values (30)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
19
 
8.4%
25
 
4.7%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
4001
0.9%
2941
0.9%
2061
0.9%
1791
0.9%
1692
1.9%

CGD MOLSHEIM
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.99029126
Minimum0
Maximum407
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:39:19.411855image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q329.5
95-th percentile139.5
Maximum407
Range407
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation60.43672678
Coefficient of variation (CV)2.084722993
Kurtosis17.2679018
Mean28.99029126
Median Absolute Deviation (MAD)4
Skewness3.753891923
Sum2986
Variance3652.597944
MonotocityNot monotonic
2021-02-18T22:39:19.518716image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
033
30.8%
111
 
10.3%
45
 
4.7%
34
 
3.7%
103
 
2.8%
23
 
2.8%
182
 
1.9%
302
 
1.9%
262
 
1.9%
222
 
1.9%
Other values (36)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
111
 
10.3%
23
 
2.8%
34
 
3.7%
45
 
4.7%
ValueCountFrequency (%)
4071
0.9%
2611
0.9%
2131
0.9%
2081
0.9%
1561
0.9%

CGD SAVERNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.42718447
Minimum0
Maximum281
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:19.625979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q323
95-th percentile109.4
Maximum281
Range281
Interquartile range (IQR)23

Descriptive statistics

Standard deviation44.4139622
Coefficient of variation (CV)1.980362817
Kurtosis14.26485648
Mean22.42718447
Median Absolute Deviation (MAD)4
Skewness3.439945263
Sum2310
Variance1972.600038
MonotocityNot monotonic
2021-02-18T22:39:19.729753image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
031
29.0%
110
 
9.3%
35
 
4.7%
24
 
3.7%
53
 
2.8%
103
 
2.8%
162
 
1.9%
42
 
1.9%
112
 
1.9%
132
 
1.9%
Other values (35)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
110
 
9.3%
24
 
3.7%
35
 
4.7%
42
 
1.9%
ValueCountFrequency (%)
2811
0.9%
2161
0.9%
1471
0.9%
1261
0.9%
1161
0.9%

CGD SELESTAT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean30.81553398
Minimum0
Maximum416
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:19.854306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q326
95-th percentile141.5
Maximum416
Range416
Interquartile range (IQR)26

Descriptive statistics

Standard deviation64.868154
Coefficient of variation (CV)2.105047216
Kurtosis16.19904389
Mean30.81553398
Median Absolute Deviation (MAD)4
Skewness3.689018688
Sum3174
Variance4207.877403
MonotocityNot monotonic
2021-02-18T22:39:19.950869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
030
28.0%
37
 
6.5%
16
 
5.6%
25
 
4.7%
44
 
3.7%
263
 
2.8%
63
 
2.8%
643
 
2.8%
133
 
2.8%
52
 
1.9%
Other values (33)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
16
 
5.6%
25
 
4.7%
37
 
6.5%
44
 
3.7%
ValueCountFrequency (%)
4161
0.9%
3321
0.9%
2031
0.9%
1951
0.9%
1791
0.9%

CGD STRASBOURG
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean39.62135922
Minimum0
Maximum609
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:20.049561image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q327
95-th percentile232.9
Maximum609
Range609
Interquartile range (IQR)27

Descriptive statistics

Standard deviation88.77224841
Coefficient of variation (CV)2.240514969
Kurtosis17.97069498
Mean39.62135922
Median Absolute Deviation (MAD)5
Skewness3.817692599
Sum4081
Variance7880.512088
MonotocityNot monotonic
2021-02-18T22:39:20.147997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
027
25.2%
112
 
11.2%
46
 
5.6%
184
 
3.7%
224
 
3.7%
64
 
3.7%
53
 
2.8%
23
 
2.8%
112
 
1.9%
122
 
1.9%
Other values (34)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
112
11.2%
23
 
2.8%
31
 
0.9%
46
 
5.6%
ValueCountFrequency (%)
6091
0.9%
3241
0.9%
2991
0.9%
2781
0.9%
2751
0.9%

CGD WISSEMBOURG
Real number (ℝ≥0)

MISSING
ZEROS

Distinct30
Distinct (%)29.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean10.57281553
Minimum0
Maximum173
Zeros40
Zeros (%)37.4%
Memory size984.0 B
2021-02-18T22:39:20.248175image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q37.5
95-th percentile54.9
Maximum173
Range173
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation24.57545481
Coefficient of variation (CV)2.324400226
Kurtosis22.04064946
Mean10.57281553
Median Absolute Deviation (MAD)2
Skewness4.273542012
Sum1089
Variance603.9529792
MonotocityNot monotonic
2021-02-18T22:39:20.345675image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
040
37.4%
111
 
10.3%
77
 
6.5%
36
 
5.6%
25
 
4.7%
43
 
2.8%
83
 
2.8%
63
 
2.8%
202
 
1.9%
112
 
1.9%
Other values (20)21
19.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
040
37.4%
111
 
10.3%
25
 
4.7%
36
 
5.6%
43
 
2.8%
ValueCountFrequency (%)
1731
0.9%
1181
0.9%
841
0.9%
671
0.9%
591
0.9%

CGD ALTKIRCH
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.89320388
Minimum0
Maximum332
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:39:20.452441image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q320.5
95-th percentile95.2
Maximum332
Range332
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation43.22533585
Coefficient of variation (CV)2.172869494
Kurtosis27.24693374
Mean19.89320388
Median Absolute Deviation (MAD)3
Skewness4.517261983
Sum2049
Variance1868.429659
MonotocityNot monotonic
2021-02-18T22:39:20.552743image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
037
34.6%
19
 
8.4%
24
 
3.7%
34
 
3.7%
93
 
2.8%
63
 
2.8%
152
 
1.9%
122
 
1.9%
42
 
1.9%
282
 
1.9%
Other values (30)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
19
 
8.4%
24
 
3.7%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
3321
0.9%
1601
0.9%
1171
0.9%
1121
0.9%
1021
0.9%

CGD COLMAR
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.99029126
Minimum0
Maximum408
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:20.661908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q331.5
95-th percentile164.9
Maximum408
Range408
Interquartile range (IQR)31.5

Descriptive statistics

Standard deviation59.50490096
Coefficient of variation (CV)2.052580308
Kurtosis17.33659813
Mean28.99029126
Median Absolute Deviation (MAD)6
Skewness3.700598962
Sum2986
Variance3540.833238
MonotocityNot monotonic
2021-02-18T22:39:20.775283image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
034
31.8%
17
 
6.5%
34
 
3.7%
84
 
3.7%
103
 
2.8%
63
 
2.8%
42
 
1.9%
292
 
1.9%
362
 
1.9%
112
 
1.9%
Other values (35)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
17
 
6.5%
22
 
1.9%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
4081
0.9%
2351
0.9%
1811
0.9%
1781
0.9%
1721
0.9%

CGD MULHOUSE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean39.2815534
Minimum0
Maximum464
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:39:20.888006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q333
95-th percentile212.2
Maximum464
Range464
Interquartile range (IQR)33

Descriptive statistics

Standard deviation78.14885463
Coefficient of variation (CV)1.989454282
Kurtosis11.1064934
Mean39.2815534
Median Absolute Deviation (MAD)8
Skewness3.116858238
Sum4046
Variance6107.24348
MonotocityNot monotonic
2021-02-18T22:39:21.023913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
028
26.2%
19
 
8.4%
84
 
3.7%
104
 
3.7%
53
 
2.8%
333
 
2.8%
203
 
2.8%
113
 
2.8%
73
 
2.8%
242
 
1.9%
Other values (35)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
19
 
8.4%
22
 
1.9%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
4641
0.9%
3601
0.9%
2531
0.9%
2471
0.9%
2301
0.9%

CGD SOULTZ GUEBWILLER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean35.29126214
Minimum0
Maximum451
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:21.140957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q336
95-th percentile179.3
Maximum451
Range451
Interquartile range (IQR)36

Descriptive statistics

Standard deviation72.89915558
Coefficient of variation (CV)2.065643198
Kurtosis15.58512905
Mean35.29126214
Median Absolute Deviation (MAD)5
Skewness3.616961366
Sum3635
Variance5314.286884
MonotocityNot monotonic
2021-02-18T22:39:21.243021image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
030
28.0%
27
 
6.5%
17
 
6.5%
34
 
3.7%
43
 
2.8%
83
 
2.8%
462
 
1.9%
62
 
1.9%
362
 
1.9%
412
 
1.9%
Other values (38)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
17
 
6.5%
27
 
6.5%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
4511
0.9%
3991
0.9%
2021
0.9%
2011
0.9%
1971
0.9%

CGD BRON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean45.37864078
Minimum0
Maximum469
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:39:21.345051image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q331.5
95-th percentile236.9
Maximum469
Range469
Interquartile range (IQR)31.5

Descriptive statistics

Standard deviation95.8621474
Coefficient of variation (CV)2.112494904
Kurtosis8.749396433
Mean45.37864078
Median Absolute Deviation (MAD)5
Skewness2.937729827
Sum4674
Variance9189.551304
MonotocityNot monotonic
2021-02-18T22:39:21.446609image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
029
27.1%
19
 
8.4%
35
 
4.7%
24
 
3.7%
54
 
3.7%
63
 
2.8%
93
 
2.8%
43
 
2.8%
172
 
1.9%
562
 
1.9%
Other values (35)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
19
 
8.4%
24
 
3.7%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
4691
0.9%
4511
0.9%
4321
0.9%
3161
0.9%
3081
0.9%

CGD GIVORS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean56.75728155
Minimum0
Maximum699
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:39:21.550396image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median7
Q341
95-th percentile292.7
Maximum699
Range699
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation122.6171681
Coefficient of variation (CV)2.160377749
Kurtosis12.78164117
Mean56.75728155
Median Absolute Deviation (MAD)7
Skewness3.403548091
Sum5846
Variance15034.96992
MonotocityNot monotonic
2021-02-18T22:39:21.655729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
026
24.3%
110
 
9.3%
27
 
6.5%
44
 
3.7%
243
 
2.8%
73
 
2.8%
82
 
1.9%
292
 
1.9%
132
 
1.9%
32
 
1.9%
Other values (39)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
110
 
9.3%
27
 
6.5%
32
 
1.9%
44
 
3.7%
ValueCountFrequency (%)
6991
0.9%
6301
0.9%
5121
0.9%
3711
0.9%
3471
0.9%

CGD L ARBRESLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct51
Distinct (%)49.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean62.01941748
Minimum0
Maximum630
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:21.767224image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q352.5
95-th percentile395.6
Maximum630
Range630
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation128.7675349
Coefficient of variation (CV)2.076245475
Kurtosis8.406838069
Mean62.01941748
Median Absolute Deviation (MAD)7
Skewness2.923329389
Sum6388
Variance16581.07805
MonotocityNot monotonic
2021-02-18T22:39:21.871703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
027
25.2%
18
 
7.5%
36
 
5.6%
24
 
3.7%
63
 
2.8%
142
 
1.9%
102
 
1.9%
122
 
1.9%
72
 
1.9%
352
 
1.9%
Other values (41)45
42.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
18
 
7.5%
24
 
3.7%
36
 
5.6%
41
 
0.9%
ValueCountFrequency (%)
6301
0.9%
5951
0.9%
5531
0.9%
4411
0.9%
4091
0.9%

CGD LYON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean40.34951456
Minimum0
Maximum454
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:39:21.981323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median4
Q333
95-th percentile210.5
Maximum454
Range454
Interquartile range (IQR)32.5

Descriptive statistics

Standard deviation85.2188312
Coefficient of variation (CV)2.112016269
Kurtosis11.45264525
Mean40.34951456
Median Absolute Deviation (MAD)4
Skewness3.278580424
Sum4156
Variance7262.249191
MonotocityNot monotonic
2021-02-18T22:39:22.080607image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
026
24.3%
210
 
9.3%
19
 
8.4%
34
 
3.7%
44
 
3.7%
93
 
2.8%
163
 
2.8%
142
 
1.9%
322
 
1.9%
332
 
1.9%
Other values (35)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
19
 
8.4%
210
 
9.3%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
4541
0.9%
4181
0.9%
4041
0.9%
2701
0.9%
2541
0.9%

CGD VILLEFRANCHE SUR SAONE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean43.98058252
Minimum0
Maximum577
Zeros19
Zeros (%)17.8%
Memory size984.0 B
2021-02-18T22:39:22.184293image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q335.5
95-th percentile216.6
Maximum577
Range577
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation89.25508505
Coefficient of variation (CV)2.029420256
Kurtosis14.54096227
Mean43.98058252
Median Absolute Deviation (MAD)8
Skewness3.477975489
Sum4530
Variance7966.470208
MonotocityNot monotonic
2021-02-18T22:39:22.307854image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
019
17.8%
114
 
13.1%
35
 
4.7%
45
 
4.7%
24
 
3.7%
83
 
2.8%
253
 
2.8%
143
 
2.8%
122
 
1.9%
202
 
1.9%
Other values (39)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
019
17.8%
114
13.1%
24
 
3.7%
35
 
4.7%
45
 
4.7%
ValueCountFrequency (%)
5771
0.9%
3542
1.9%
2941
0.9%
2591
0.9%
2171
0.9%

CGD LURE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.11650485
Minimum0
Maximum376
Zeros23
Zeros (%)21.5%
Memory size984.0 B
2021-02-18T22:39:22.435442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q325
95-th percentile131
Maximum376
Range376
Interquartile range (IQR)24

Descriptive statistics

Standard deviation57.68309314
Coefficient of variation (CV)2.127231863
Kurtosis17.29774836
Mean27.11650485
Median Absolute Deviation (MAD)4
Skewness3.807440463
Sum2793
Variance3327.339235
MonotocityNot monotonic
2021-02-18T22:39:22.538622image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
023
21.5%
114
 
13.1%
28
 
7.5%
34
 
3.7%
44
 
3.7%
133
 
2.8%
53
 
2.8%
112
 
1.9%
142
 
1.9%
1222
 
1.9%
Other values (34)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
023
21.5%
114
13.1%
28
 
7.5%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
3761
0.9%
2971
0.9%
1901
0.9%
1691
0.9%
1341
0.9%

CGD VESOUL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean29.81553398
Minimum0
Maximum434
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:39:22.646615image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q325
95-th percentile122.9
Maximum434
Range434
Interquartile range (IQR)25

Descriptive statistics

Standard deviation62.74282204
Coefficient of variation (CV)2.104366874
Kurtosis19.21464509
Mean29.81553398
Median Absolute Deviation (MAD)5
Skewness3.931440422
Sum3071
Variance3936.661717
MonotocityNot monotonic
2021-02-18T22:39:22.760800image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
028
26.2%
112
 
11.2%
25
 
4.7%
224
 
3.7%
34
 
3.7%
133
 
2.8%
123
 
2.8%
1222
 
1.9%
252
 
1.9%
232
 
1.9%
Other values (32)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
112
11.2%
25
 
4.7%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
4341
0.9%
2781
0.9%
2331
0.9%
1821
0.9%
1331
0.9%

CGD AUTUN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct33
Distinct (%)32.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean13.69902913
Minimum0
Maximum151
Zeros39
Zeros (%)36.4%
Memory size984.0 B
2021-02-18T22:39:22.886651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q314.5
95-th percentile70
Maximum151
Range151
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation25.80501355
Coefficient of variation (CV)1.883711124
Kurtosis9.885690054
Mean13.69902913
Median Absolute Deviation (MAD)1
Skewness2.942329482
Sum1411
Variance665.8987245
MonotocityNot monotonic
2021-02-18T22:39:22.994230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
039
36.4%
113
 
12.1%
36
 
5.6%
114
 
3.7%
63
 
2.8%
82
 
1.9%
702
 
1.9%
232
 
1.9%
142
 
1.9%
52
 
1.9%
Other values (23)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
039
36.4%
113
 
12.1%
36
 
5.6%
52
 
1.9%
63
 
2.8%
ValueCountFrequency (%)
1511
0.9%
1111
0.9%
901
0.9%
812
1.9%
702
1.9%

CGD CHALON SUR SAONE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.96116505
Minimum0
Maximum275
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:23.090246image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q317
95-th percentile119.9
Maximum275
Range275
Interquartile range (IQR)17

Descriptive statistics

Standard deviation43.52527378
Coefficient of variation (CV)2.07647207
Kurtosis13.3045989
Mean20.96116505
Median Absolute Deviation (MAD)2
Skewness3.329626714
Sum2159
Variance1894.449457
MonotocityNot monotonic
2021-02-18T22:39:23.180601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
035
32.7%
210
 
9.3%
17
 
6.5%
34
 
3.7%
44
 
3.7%
174
 
3.7%
73
 
2.8%
123
 
2.8%
622
 
1.9%
52
 
1.9%
Other values (27)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
17
 
6.5%
210
 
9.3%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
2751
0.9%
1891
0.9%
1391
0.9%
1311
0.9%
1291
0.9%

CGD CHAROLLES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22
Minimum0
Maximum317
Zeros41
Zeros (%)38.3%
Memory size984.0 B
2021-02-18T22:39:23.278959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q320.5
95-th percentile109.7
Maximum317
Range317
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation44.3835776
Coefficient of variation (CV)2.017435346
Kurtosis19.62334245
Mean22
Median Absolute Deviation (MAD)2
Skewness3.804237027
Sum2266
Variance1969.901961
MonotocityNot monotonic
2021-02-18T22:39:23.376314image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
041
38.3%
27
 
6.5%
164
 
3.7%
54
 
3.7%
14
 
3.7%
133
 
2.8%
93
 
2.8%
232
 
1.9%
32
 
1.9%
152
 
1.9%
Other values (30)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
041
38.3%
14
 
3.7%
27
 
6.5%
32
 
1.9%
41
 
0.9%
ValueCountFrequency (%)
3171
0.9%
1641
0.9%
1391
0.9%
1181
0.9%
1131
0.9%

CGD LOUHANS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.00970874
Minimum0
Maximum161
Zeros41
Zeros (%)38.3%
Memory size984.0 B
2021-02-18T22:39:23.475381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q312
95-th percentile71.9
Maximum161
Range161
Interquartile range (IQR)12

Descriptive statistics

Standard deviation33.50928907
Coefficient of variation (CV)2.093060506
Kurtosis9.1904387
Mean16.00970874
Median Absolute Deviation (MAD)2
Skewness3.030129154
Sum1649
Variance1122.872454
MonotocityNot monotonic
2021-02-18T22:39:23.570192image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
041
38.3%
110
 
9.3%
25
 
4.7%
44
 
3.7%
114
 
3.7%
84
 
3.7%
93
 
2.8%
132
 
1.9%
1522
 
1.9%
52
 
1.9%
Other values (24)26
24.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
041
38.3%
110
 
9.3%
25
 
4.7%
32
 
1.9%
44
 
3.7%
ValueCountFrequency (%)
1611
0.9%
1522
1.9%
1331
0.9%
1251
0.9%
721
0.9%

CGD MACON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean21.58252427
Minimum0
Maximum305
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:39:23.673370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q315
95-th percentile112.9
Maximum305
Range305
Interquartile range (IQR)15

Descriptive statistics

Standard deviation44.84516374
Coefficient of variation (CV)2.077846093
Kurtosis16.34733479
Mean21.58252427
Median Absolute Deviation (MAD)3
Skewness3.563019492
Sum2223
Variance2011.088711
MonotocityNot monotonic
2021-02-18T22:39:23.770005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
037
34.6%
110
 
9.3%
137
 
6.5%
34
 
3.7%
43
 
2.8%
92
 
1.9%
482
 
1.9%
22
 
1.9%
142
 
1.9%
102
 
1.9%
Other values (30)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
110
 
9.3%
22
 
1.9%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
3051
0.9%
1571
0.9%
1531
0.9%
1271
0.9%
1211
0.9%

CGD LA FLECHE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct51
Distinct (%)49.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean41.10679612
Minimum0
Maximum499
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:39:23.874535image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median4
Q350.5
95-th percentile189.5
Maximum499
Range499
Interquartile range (IQR)50

Descriptive statistics

Standard deviation78.64525871
Coefficient of variation (CV)1.913193587
Kurtosis13.02737993
Mean41.10679612
Median Absolute Deviation (MAD)4
Skewness3.228155793
Sum4234
Variance6185.076718
MonotocityNot monotonic
2021-02-18T22:39:23.985990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
026
24.3%
111
 
10.3%
210
 
9.3%
33
 
2.8%
43
 
2.8%
1502
 
1.9%
322
 
1.9%
242
 
1.9%
82
 
1.9%
811
 
0.9%
Other values (41)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
111
10.3%
210
 
9.3%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
4991
0.9%
3491
0.9%
2551
0.9%
2431
0.9%
2221
0.9%

CGD LE MANS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean58.99029126
Minimum0
Maximum1008
Zeros23
Zeros (%)21.5%
Memory size984.0 B
2021-02-18T22:39:24.096048image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q355
95-th percentile270.9
Maximum1008
Range1008
Interquartile range (IQR)54

Descriptive statistics

Standard deviation130.1781204
Coefficient of variation (CV)2.206771956
Kurtosis28.14061569
Mean58.99029126
Median Absolute Deviation (MAD)5
Skewness4.568916173
Sum6076
Variance16946.34304
MonotocityNot monotonic
2021-02-18T22:39:24.208035image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
023
21.5%
114
 
13.1%
27
 
6.5%
33
 
2.8%
53
 
2.8%
193
 
2.8%
102
 
1.9%
802
 
1.9%
82
 
1.9%
452
 
1.9%
Other values (40)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
023
21.5%
114
13.1%
27
 
6.5%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
10081
0.9%
4641
0.9%
3851
0.9%
2881
0.9%
2861
0.9%

CGD MAMERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.41747573
Minimum0
Maximum284
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:39:24.333730image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q322.5
95-th percentile101.8
Maximum284
Range284
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation45.08891527
Coefficient of variation (CV)2.011328832
Kurtosis15.21792434
Mean22.41747573
Median Absolute Deviation (MAD)2
Skewness3.496153065
Sum2309
Variance2033.01028
MonotocityNot monotonic
2021-02-18T22:39:24.443142image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
038
35.5%
111
 
10.3%
25
 
4.7%
53
 
2.8%
133
 
2.8%
242
 
1.9%
342
 
1.9%
72
 
1.9%
112
 
1.9%
82
 
1.9%
Other values (29)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
111
 
10.3%
25
 
4.7%
32
 
1.9%
53
 
2.8%
ValueCountFrequency (%)
2841
0.9%
2391
0.9%
1271
0.9%
1141
0.9%
1101
0.9%

CGD ALBERTVILLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean44.38834951
Minimum0
Maximum981
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:24.548278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q328.5
95-th percentile170.3
Maximum981
Range981
Interquartile range (IQR)28.5

Descriptive statistics

Standard deviation122.1495574
Coefficient of variation (CV)2.751838235
Kurtosis36.78678412
Mean44.38834951
Median Absolute Deviation (MAD)5
Skewness5.53492995
Sum4572
Variance14920.51437
MonotocityNot monotonic
2021-02-18T22:39:24.683615image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
032
29.9%
17
 
6.5%
25
 
4.7%
34
 
3.7%
43
 
2.8%
123
 
2.8%
53
 
2.8%
102
 
1.9%
252
 
1.9%
562
 
1.9%
Other values (34)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
17
 
6.5%
25
 
4.7%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
9811
0.9%
5591
0.9%
3281
0.9%
3151
0.9%
2381
0.9%

CGD CHAMBERY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean46.48543689
Minimum0
Maximum687
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:24.800182image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q333.5
95-th percentile251.9
Maximum687
Range687
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation101.7227936
Coefficient of variation (CV)2.188272294
Kurtosis17.50288909
Mean46.48543689
Median Absolute Deviation (MAD)6
Skewness3.804354339
Sum4788
Variance10347.52675
MonotocityNot monotonic
2021-02-18T22:39:24.903951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
027
25.2%
110
 
9.3%
34
 
3.7%
54
 
3.7%
213
 
2.8%
123
 
2.8%
103
 
2.8%
23
 
2.8%
352
 
1.9%
142
 
1.9%
Other values (37)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
110
 
9.3%
23
 
2.8%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
6871
0.9%
3911
0.9%
3801
0.9%
3711
0.9%
2791
0.9%

CGD ST JEAN DE MAURIENNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)33.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.63106796
Minimum0
Maximum193
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:39:25.011423image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q316
95-th percentile87.3
Maximum193
Range193
Interquartile range (IQR)16

Descriptive statistics

Standard deviation33.28957627
Coefficient of variation (CV)2.001649945
Kurtosis11.82366741
Mean16.63106796
Median Absolute Deviation (MAD)4
Skewness3.235041984
Sum1713
Variance1108.195888
MonotocityNot monotonic
2021-02-18T22:39:25.120873image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
036
33.6%
18
 
7.5%
57
 
6.5%
45
 
4.7%
83
 
2.8%
143
 
2.8%
173
 
2.8%
73
 
2.8%
33
 
2.8%
23
 
2.8%
Other values (24)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
18
 
7.5%
23
 
2.8%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
1931
0.9%
1681
0.9%
1171
0.9%
1051
0.9%
1011
0.9%

CGD ANNECY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct56
Distinct (%)54.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean80.24271845
Minimum0
Maximum1011
Zeros23
Zeros (%)21.5%
Memory size984.0 B
2021-02-18T22:39:25.267937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median11
Q363
95-th percentile519.5
Maximum1011
Range1011
Interquartile range (IQR)62

Descriptive statistics

Standard deviation173.4655679
Coefficient of variation (CV)2.161760859
Kurtosis12.02678521
Mean80.24271845
Median Absolute Deviation (MAD)11
Skewness3.35239099
Sum8265
Variance30090.30326
MonotocityNot monotonic
2021-02-18T22:39:25.392930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
023
21.5%
18
 
7.5%
44
 
3.7%
54
 
3.7%
344
 
3.7%
114
 
3.7%
24
 
3.7%
62
 
1.9%
562
 
1.9%
1322
 
1.9%
Other values (46)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
023
21.5%
18
 
7.5%
24
 
3.7%
31
 
0.9%
44
 
3.7%
ValueCountFrequency (%)
10111
0.9%
8131
0.9%
6121
0.9%
6071
0.9%
5581
0.9%

CGD BONNEVILLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean49.22330097
Minimum0
Maximum549
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:39:25.498936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q352.5
95-th percentile259.3
Maximum549
Range549
Interquartile range (IQR)51.5

Descriptive statistics

Standard deviation98.83745143
Coefficient of variation (CV)2.007940335
Kurtosis10.48934241
Mean49.22330097
Median Absolute Deviation (MAD)6
Skewness3.105399257
Sum5070
Variance9768.841805
MonotocityNot monotonic
2021-02-18T22:39:25.600064image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
024
22.4%
110
 
9.3%
25
 
4.7%
35
 
4.7%
53
 
2.8%
143
 
2.8%
113
 
2.8%
63
 
2.8%
272
 
1.9%
42
 
1.9%
Other values (40)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
110
9.3%
25
 
4.7%
35
 
4.7%
42
 
1.9%
ValueCountFrequency (%)
5491
0.9%
4901
0.9%
3561
0.9%
3391
0.9%
2651
0.9%

CGD CHAMONIX MONT BLANC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.97087379
Minimum0
Maximum362
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:25.724785image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q321.5
95-th percentile130.1
Maximum362
Range362
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation59.28172292
Coefficient of variation (CV)2.197990447
Kurtosis14.49203386
Mean26.97087379
Median Absolute Deviation (MAD)4
Skewness3.620075701
Sum2778
Variance3514.322673
MonotocityNot monotonic
2021-02-18T22:39:25.855204image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
031
29.0%
38
 
7.5%
17
 
6.5%
25
 
4.7%
103
 
2.8%
53
 
2.8%
112
 
1.9%
392
 
1.9%
182
 
1.9%
132
 
1.9%
Other values (31)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
17
 
6.5%
25
 
4.7%
38
 
7.5%
42
 
1.9%
ValueCountFrequency (%)
3621
0.9%
2881
0.9%
2271
0.9%
2011
0.9%
1981
0.9%

CGD ST JULIEN EN GENEVOIS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean46.30097087
Minimum0
Maximum611
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:25.973504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q345.5
95-th percentile288.4
Maximum611
Range611
Interquartile range (IQR)45.5

Descriptive statistics

Standard deviation102.1778376
Coefficient of variation (CV)2.206818467
Kurtosis13.61029278
Mean46.30097087
Median Absolute Deviation (MAD)7
Skewness3.548113129
Sum4769
Variance10440.31049
MonotocityNot monotonic
2021-02-18T22:39:26.074768image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
027
25.2%
110
 
9.3%
37
 
6.5%
193
 
2.8%
93
 
2.8%
23
 
2.8%
432
 
1.9%
62
 
1.9%
532
 
1.9%
662
 
1.9%
Other values (37)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
110
 
9.3%
23
 
2.8%
37
 
6.5%
42
 
1.9%
ValueCountFrequency (%)
6111
0.9%
4751
0.9%
4361
0.9%
3211
0.9%
3141
0.9%

CGD THONON LES BAINS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean29.34951456
Minimum0
Maximum353
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:39:26.182818image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q322.5
95-th percentile146.1
Maximum353
Range353
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation64.42455821
Coefficient of variation (CV)2.195080879
Kurtosis12.56382141
Mean29.34951456
Median Absolute Deviation (MAD)5
Skewness3.45449841
Sum3023
Variance4150.523701
MonotocityNot monotonic
2021-02-18T22:39:26.312541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
028
26.2%
112
 
11.2%
65
 
4.7%
24
 
3.7%
44
 
3.7%
134
 
3.7%
33
 
2.8%
143
 
2.8%
102
 
1.9%
112
 
1.9%
Other values (32)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
112
11.2%
24
 
3.7%
33
 
2.8%
44
 
3.7%
ValueCountFrequency (%)
3531
0.9%
3361
0.9%
2591
0.9%
2441
0.9%
1911
0.9%

CGD DIEPPE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.86407767
Minimum0
Maximum248
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:39:26.446700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q317
95-th percentile79.9
Maximum248
Range248
Interquartile range (IQR)17

Descriptive statistics

Standard deviation36.99444806
Coefficient of variation (CV)2.070884864
Kurtosis18.11605267
Mean17.86407767
Median Absolute Deviation (MAD)2
Skewness3.795502079
Sum1840
Variance1368.589187
MonotocityNot monotonic
2021-02-18T22:39:26.573668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
037
34.6%
112
 
11.2%
26
 
5.6%
115
 
4.7%
103
 
2.8%
63
 
2.8%
202
 
1.9%
572
 
1.9%
42
 
1.9%
82
 
1.9%
Other values (28)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
112
 
11.2%
26
 
5.6%
31
 
0.9%
42
 
1.9%
ValueCountFrequency (%)
2481
0.9%
1891
0.9%
1031
0.9%
891
0.9%
831
0.9%

CGD FECAMP
Real number (ℝ≥0)

MISSING
ZEROS

Distinct32
Distinct (%)31.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean14.63106796
Minimum0
Maximum184
Zeros36
Zeros (%)33.6%
Memory size984.0 B
2021-02-18T22:39:26.672086image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q312
95-th percentile72.2
Maximum184
Range184
Interquartile range (IQR)12

Descriptive statistics

Standard deviation29.78715024
Coefficient of variation (CV)2.035883527
Kurtosis13.56267611
Mean14.63106796
Median Absolute Deviation (MAD)2
Skewness3.426578362
Sum1507
Variance887.2743194
MonotocityNot monotonic
2021-02-18T22:39:26.785186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
036
33.6%
19
 
8.4%
27
 
6.5%
55
 
4.7%
105
 
4.7%
34
 
3.7%
94
 
3.7%
243
 
2.8%
83
 
2.8%
132
 
1.9%
Other values (22)25
23.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
036
33.6%
19
 
8.4%
27
 
6.5%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
1841
0.9%
1351
0.9%
1151
0.9%
1121
0.9%
751
0.9%

CGD LE HAVRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct32
Distinct (%)31.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.19417476
Minimum0
Maximum203
Zeros41
Zeros (%)38.3%
Memory size984.0 B
2021-02-18T22:39:26.917131image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q316
95-th percentile87.9
Maximum203
Range203
Interquartile range (IQR)16

Descriptive statistics

Standard deviation34.83801683
Coefficient of variation (CV)2.026152306
Kurtosis9.916024977
Mean17.19417476
Median Absolute Deviation (MAD)2
Skewness2.978970576
Sum1771
Variance1213.687417
MonotocityNot monotonic
2021-02-18T22:39:27.032114image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
041
38.3%
28
 
7.5%
17
 
6.5%
193
 
2.8%
103
 
2.8%
43
 
2.8%
53
 
2.8%
63
 
2.8%
93
 
2.8%
212
 
1.9%
Other values (22)27
25.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
041
38.3%
17
 
6.5%
28
 
7.5%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
2031
0.9%
1351
0.9%
1321
0.9%
1231
0.9%
1061
0.9%

CGD NEUFCHATEL EN BRAY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.25242718
Minimum0
Maximum290
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:39:27.141558image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q322
95-th percentile132.6
Maximum290
Range290
Interquartile range (IQR)22

Descriptive statistics

Standard deviation51.71617839
Coefficient of variation (CV)1.969957978
Kurtosis10.95935627
Mean26.25242718
Median Absolute Deviation (MAD)4
Skewness3.071476623
Sum2704
Variance2674.563107
MonotocityNot monotonic
2021-02-18T22:39:27.241299image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
033
30.8%
112
 
11.2%
55
 
4.7%
74
 
3.7%
44
 
3.7%
183
 
2.8%
23
 
2.8%
172
 
1.9%
142
 
1.9%
232
 
1.9%
Other values (32)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
112
 
11.2%
23
 
2.8%
31
 
0.9%
44
 
3.7%
ValueCountFrequency (%)
2901
0.9%
2731
0.9%
1611
0.9%
1501
0.9%
1411
0.9%

CGD ROUEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean30.93203883
Minimum0
Maximum406
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:27.358554image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q319
95-th percentile168
Maximum406
Range406
Interquartile range (IQR)19

Descriptive statistics

Standard deviation64.18039254
Coefficient of variation (CV)2.074884002
Kurtosis13.15385457
Mean30.93203883
Median Absolute Deviation (MAD)3
Skewness3.293750811
Sum3186
Variance4119.122787
MonotocityNot monotonic
2021-02-18T22:39:27.495138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
030
28.0%
113
12.1%
27
 
6.5%
34
 
3.7%
134
 
3.7%
43
 
2.8%
173
 
2.8%
113
 
2.8%
162
 
1.9%
822
 
1.9%
Other values (29)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
113
12.1%
27
 
6.5%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
4061
0.9%
2601
0.9%
2431
0.9%
1871
0.9%
1841
0.9%

CGD YVETOT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.73786408
Minimum0
Maximum263
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:39:27.621846image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q319.5
95-th percentile114.7
Maximum263
Range263
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation46.13852993
Coefficient of variation (CV)2.029149694
Kurtosis11.10141631
Mean22.73786408
Median Absolute Deviation (MAD)4
Skewness3.162691627
Sum2342
Variance2128.763944
MonotocityNot monotonic
2021-02-18T22:39:27.721565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
037
34.6%
17
 
6.5%
35
 
4.7%
44
 
3.7%
134
 
3.7%
213
 
2.8%
53
 
2.8%
123
 
2.8%
63
 
2.8%
152
 
1.9%
Other values (28)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
17
 
6.5%
21
 
0.9%
35
 
4.7%
44
 
3.7%
ValueCountFrequency (%)
2631
0.9%
2231
0.9%
1851
0.9%
1421
0.9%
1321
0.9%

CGD COULOMMIERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean41.4368932
Minimum0
Maximum438
Zeros22
Zeros (%)20.6%
Memory size984.0 B
2021-02-18T22:39:27.829382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q335
95-th percentile220.1
Maximum438
Range438
Interquartile range (IQR)34

Descriptive statistics

Standard deviation79.37743912
Coefficient of variation (CV)1.915622359
Kurtosis8.783863449
Mean41.4368932
Median Absolute Deviation (MAD)6
Skewness2.845340633
Sum4268
Variance6300.777841
MonotocityNot monotonic
2021-02-18T22:39:27.934673image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
022
20.6%
110
 
9.3%
28
 
7.5%
45
 
4.7%
35
 
4.7%
234
 
3.7%
92
 
1.9%
312
 
1.9%
122
 
1.9%
242
 
1.9%
Other values (40)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
022
20.6%
110
9.3%
28
 
7.5%
35
 
4.7%
45
 
4.7%
ValueCountFrequency (%)
4381
0.9%
3591
0.9%
3061
0.9%
2261
0.9%
2241
0.9%

CGD FONTAINEBLEAU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean15.96116505
Minimum0
Maximum148
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:39:28.062086image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q315
95-th percentile80.2
Maximum148
Range148
Interquartile range (IQR)15

Descriptive statistics

Standard deviation29.61051825
Coefficient of variation (CV)1.855160206
Kurtosis8.031214443
Mean15.96116505
Median Absolute Deviation (MAD)4
Skewness2.804223714
Sum1644
Variance876.7827908
MonotocityNot monotonic
2021-02-18T22:39:28.186819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
033
30.8%
18
 
7.5%
47
 
6.5%
25
 
4.7%
75
 
4.7%
65
 
4.7%
83
 
2.8%
93
 
2.8%
1172
 
1.9%
322
 
1.9%
Other values (26)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
18
 
7.5%
25
 
4.7%
47
 
6.5%
52
 
1.9%
ValueCountFrequency (%)
1481
0.9%
1391
0.9%
1172
1.9%
921
0.9%
811
0.9%

CGD MEAUX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean38.80582524
Minimum0
Maximum357
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:39:28.324094image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.5
median10
Q329
95-th percentile216.9
Maximum357
Range357
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation73.03827337
Coefficient of variation (CV)1.88214715
Kurtosis6.446579321
Mean38.80582524
Median Absolute Deviation (MAD)10
Skewness2.594623539
Sum3997
Variance5334.589377
MonotocityNot monotonic
2021-02-18T22:39:28.460069image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
025
23.4%
211
 
10.3%
45
 
4.7%
34
 
3.7%
194
 
3.7%
212
 
1.9%
272
 
1.9%
102
 
1.9%
252
 
1.9%
142
 
1.9%
Other values (38)44
41.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
11
 
0.9%
211
10.3%
34
 
3.7%
45
 
4.7%
ValueCountFrequency (%)
3571
0.9%
3211
0.9%
2781
0.9%
2411
0.9%
2371
0.9%

CGD MELUN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean31.33009709
Minimum0
Maximum655
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:28.589284image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q320.5
95-th percentile140
Maximum655
Range655
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation77.74926875
Coefficient of variation (CV)2.481615953
Kurtosis41.28985624
Mean31.33009709
Median Absolute Deviation (MAD)7
Skewness5.687012106
Sum3227
Variance6044.948791
MonotocityNot monotonic
2021-02-18T22:39:28.713883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
027
25.2%
111
 
10.3%
24
 
3.7%
124
 
3.7%
34
 
3.7%
113
 
2.8%
93
 
2.8%
73
 
2.8%
133
 
2.8%
53
 
2.8%
Other values (34)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
111
10.3%
24
 
3.7%
34
 
3.7%
41
 
0.9%
ValueCountFrequency (%)
6551
0.9%
2561
0.9%
1981
0.9%
1921
0.9%
1571
0.9%

CGD PROVINS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean17.65048544
Minimum0
Maximum190
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:28.845524image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q318.5
95-th percentile77.8
Maximum190
Range190
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation32.48852248
Coefficient of variation (CV)1.840658864
Kurtosis9.446332367
Mean17.65048544
Median Absolute Deviation (MAD)3
Skewness2.855542059
Sum1818
Variance1055.504093
MonotocityNot monotonic
2021-02-18T22:39:28.940011image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
27
 
6.5%
46
 
5.6%
213
 
2.8%
33
 
2.8%
62
 
1.9%
172
 
1.9%
652
 
1.9%
72
 
1.9%
Other values (27)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
27
 
6.5%
33
 
2.8%
46
 
5.6%
ValueCountFrequency (%)
1901
0.9%
1281
0.9%
1221
0.9%
1201
0.9%
881
0.9%

CGD MANTES LA JOLIE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean29.62135922
Minimum0
Maximum321
Zeros22
Zeros (%)20.6%
Memory size984.0 B
2021-02-18T22:39:29.047086image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q325.5
95-th percentile159.4
Maximum321
Range321
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation57.4874439
Coefficient of variation (CV)1.940742944
Kurtosis9.742294122
Mean29.62135922
Median Absolute Deviation (MAD)8
Skewness3.016177591
Sum3051
Variance3304.806206
MonotocityNot monotonic
2021-02-18T22:39:29.150426image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
022
20.6%
115
 
14.0%
86
 
5.6%
124
 
3.7%
34
 
3.7%
24
 
3.7%
53
 
2.8%
143
 
2.8%
302
 
1.9%
222
 
1.9%
Other values (36)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
022
20.6%
115
14.0%
24
 
3.7%
34
 
3.7%
41
 
0.9%
ValueCountFrequency (%)
3211
0.9%
2561
0.9%
2331
0.9%
2011
0.9%
1641
0.9%

CGD RAMBOUILLET
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.14563107
Minimum0
Maximum315
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:29.255272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q317
95-th percentile151.2
Maximum315
Range315
Interquartile range (IQR)17

Descriptive statistics

Standard deviation54.21804341
Coefficient of variation (CV)1.997302743
Kurtosis9.871510213
Mean27.14563107
Median Absolute Deviation (MAD)4
Skewness2.98545049
Sum2796
Variance2939.596231
MonotocityNot monotonic
2021-02-18T22:39:29.352461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
145
 
4.7%
24
 
3.7%
153
 
2.8%
123
 
2.8%
33
 
2.8%
43
 
2.8%
232
 
1.9%
162
 
1.9%
Other values (30)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
24
 
3.7%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
3151
0.9%
2221
0.9%
1931
0.9%
1911
0.9%
1681
0.9%

CGD ST GERMAIN EN LAYE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.03883495
Minimum0
Maximum317
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:29.454932image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q321
95-th percentile152.6
Maximum317
Range317
Interquartile range (IQR)21

Descriptive statistics

Standard deviation53.82887233
Coefficient of variation (CV)1.99079851
Kurtosis10.03184435
Mean27.03883495
Median Absolute Deviation (MAD)4
Skewness2.98559012
Sum2785
Variance2897.547497
MonotocityNot monotonic
2021-02-18T22:39:29.552894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
027
25.2%
112
 
11.2%
35
 
4.7%
25
 
4.7%
44
 
3.7%
144
 
3.7%
63
 
2.8%
83
 
2.8%
53
 
2.8%
312
 
1.9%
Other values (30)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
112
11.2%
25
 
4.7%
35
 
4.7%
44
 
3.7%
ValueCountFrequency (%)
3171
0.9%
2111
0.9%
1911
0.9%
1821
0.9%
1761
0.9%

CGD BRESSUIRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.0776699
Minimum0
Maximum257
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:29.656005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q323.5
95-th percentile92
Maximum257
Range257
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation40.51668485
Coefficient of variation (CV)1.835188452
Kurtosis12.90645192
Mean22.0776699
Median Absolute Deviation (MAD)4
Skewness3.210440823
Sum2274
Variance1641.601751
MonotocityNot monotonic
2021-02-18T22:39:29.761194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
031
29.0%
111
 
10.3%
45
 
4.7%
24
 
3.7%
73
 
2.8%
183
 
2.8%
173
 
2.8%
113
 
2.8%
252
 
1.9%
222
 
1.9%
Other values (32)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
111
 
10.3%
24
 
3.7%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
2571
0.9%
1811
0.9%
1441
0.9%
1171
0.9%
1051
0.9%

CGD NIORT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean38.89320388
Minimum0
Maximum473
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:29.864788image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q342
95-th percentile168.3
Maximum473
Range473
Interquartile range (IQR)42

Descriptive statistics

Standard deviation74.05322842
Coefficient of variation (CV)1.90401461
Kurtosis13.34575318
Mean38.89320388
Median Absolute Deviation (MAD)6
Skewness3.258567188
Sum4006
Variance5483.88064
MonotocityNot monotonic
2021-02-18T22:39:29.969986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
24
 
3.7%
64
 
3.7%
103
 
2.8%
43
 
2.8%
222
 
1.9%
1312
 
1.9%
462
 
1.9%
242
 
1.9%
Other values (38)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
110
 
9.3%
24
 
3.7%
31
 
0.9%
43
 
2.8%
ValueCountFrequency (%)
4731
0.9%
3121
0.9%
2951
0.9%
1941
0.9%
1811
0.9%

CGD PARTHENAY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.68932039
Minimum0
Maximum202
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:30.072856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q321.5
95-th percentile87.8
Maximum202
Range202
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation36.37819567
Coefficient of variation (CV)1.84761053
Kurtosis10.33189217
Mean19.68932039
Median Absolute Deviation (MAD)3
Skewness2.976515096
Sum2028
Variance1323.37312
MonotocityNot monotonic
2021-02-18T22:39:30.195370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
035
32.7%
110
 
9.3%
55
 
4.7%
24
 
3.7%
203
 
2.8%
33
 
2.8%
153
 
2.8%
482
 
1.9%
92
 
1.9%
282
 
1.9%
Other values (28)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
110
 
9.3%
24
 
3.7%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
2021
0.9%
1901
0.9%
1251
0.9%
1161
0.9%
911
0.9%

CGD ABBEVILLE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean30.54368932
Minimum0
Maximum377
Zeros33
Zeros (%)30.8%
Memory size984.0 B
2021-02-18T22:39:30.339483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q327
95-th percentile154.2
Maximum377
Range377
Interquartile range (IQR)27

Descriptive statistics

Standard deviation61.35013251
Coefficient of variation (CV)2.008602558
Kurtosis12.97723371
Mean30.54368932
Median Absolute Deviation (MAD)5
Skewness3.301505439
Sum3146
Variance3763.838759
MonotocityNot monotonic
2021-02-18T22:39:30.480612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
033
30.8%
19
 
8.4%
25
 
4.7%
184
 
3.7%
43
 
2.8%
63
 
2.8%
192
 
1.9%
132
 
1.9%
52
 
1.9%
112
 
1.9%
Other values (35)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
033
30.8%
19
 
8.4%
25
 
4.7%
31
 
0.9%
43
 
2.8%
ValueCountFrequency (%)
3771
0.9%
2991
0.9%
1971
0.9%
1781
0.9%
1711
0.9%

CGD AMIENS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.17475728
Minimum0
Maximum249
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:30.617664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q318
95-th percentile118.5
Maximum249
Range249
Interquartile range (IQR)18

Descriptive statistics

Standard deviation44.77053197
Coefficient of variation (CV)1.931866273
Kurtosis8.850745481
Mean23.17475728
Median Absolute Deviation (MAD)3
Skewness2.81483584
Sum2387
Variance2004.400533
MonotocityNot monotonic
2021-02-18T22:39:30.734537image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
032
29.9%
113
 
12.1%
26
 
5.6%
83
 
2.8%
93
 
2.8%
103
 
2.8%
182
 
1.9%
72
 
1.9%
932
 
1.9%
52
 
1.9%
Other values (28)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
113
12.1%
26
 
5.6%
31
 
0.9%
42
 
1.9%
ValueCountFrequency (%)
2491
0.9%
2111
0.9%
1402
1.9%
1211
0.9%
1191
0.9%

CGD MONTDIDIER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.99029126
Minimum0
Maximum254
Zeros41
Zeros (%)38.3%
Memory size984.0 B
2021-02-18T22:39:30.830348image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q320
95-th percentile138.4
Maximum254
Range254
Interquartile range (IQR)20

Descriptive statistics

Standard deviation47.92487895
Coefficient of variation (CV)1.997678078
Kurtosis7.685223105
Mean23.99029126
Median Absolute Deviation (MAD)3
Skewness2.725966518
Sum2471
Variance2296.794022
MonotocityNot monotonic
2021-02-18T22:39:30.933453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
041
38.3%
35
 
4.7%
15
 
4.7%
63
 
2.8%
23
 
2.8%
203
 
2.8%
123
 
2.8%
53
 
2.8%
93
 
2.8%
112
 
1.9%
Other values (27)32
29.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
041
38.3%
15
 
4.7%
23
 
2.8%
35
 
4.7%
42
 
1.9%
ValueCountFrequency (%)
2541
0.9%
2141
0.9%
1631
0.9%
1551
0.9%
1411
0.9%

CGD PERONNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean32.51456311
Minimum0
Maximum373
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:31.058136image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q329
95-th percentile146.6
Maximum373
Range373
Interquartile range (IQR)29

Descriptive statistics

Standard deviation65.46902637
Coefficient of variation (CV)2.013529327
Kurtosis9.970477289
Mean32.51456311
Median Absolute Deviation (MAD)2
Skewness2.996373127
Sum3349
Variance4286.193413
MonotocityNot monotonic
2021-02-18T22:39:31.191466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
034
31.8%
114
13.1%
24
 
3.7%
293
 
2.8%
113
 
2.8%
103
 
2.8%
502
 
1.9%
172
 
1.9%
42
 
1.9%
52
 
1.9%
Other values (32)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
114
13.1%
24
 
3.7%
31
 
0.9%
42
 
1.9%
ValueCountFrequency (%)
3731
0.9%
2651
0.9%
2641
0.9%
2631
0.9%
1561
0.9%

CGD ALBI
Real number (ℝ≥0)

MISSING
ZEROS

Distinct29
Distinct (%)28.2%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean10.02912621
Minimum0
Maximum131
Zeros44
Zeros (%)41.1%
Memory size984.0 B
2021-02-18T22:39:31.300857image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q38.5
95-th percentile56.9
Maximum131
Range131
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation21.09105205
Coefficient of variation (CV)2.102980021
Kurtosis13.26741049
Mean10.02912621
Median Absolute Deviation (MAD)1
Skewness3.376365783
Sum1033
Variance444.8324767
MonotocityNot monotonic
2021-02-18T22:39:31.397377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
044
41.1%
18
 
7.5%
46
 
5.6%
36
 
5.6%
64
 
3.7%
203
 
2.8%
23
 
2.8%
93
 
2.8%
123
 
2.8%
52
 
1.9%
Other values (19)21
19.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
044
41.1%
18
 
7.5%
23
 
2.8%
36
 
5.6%
46
 
5.6%
ValueCountFrequency (%)
1311
0.9%
971
0.9%
681
0.9%
641
0.9%
621
0.9%

CGD CASTRES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean30.70873786
Minimum0
Maximum340
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:31.500329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q328
95-th percentile180.7
Maximum340
Range340
Interquartile range (IQR)28

Descriptive statistics

Standard deviation62.94747749
Coefficient of variation (CV)2.04982301
Kurtosis11.25400625
Mean30.70873786
Median Absolute Deviation (MAD)4
Skewness3.209782773
Sum3163
Variance3962.384923
MonotocityNot monotonic
2021-02-18T22:39:31.603662image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
030
28.0%
111
 
10.3%
26
 
5.6%
104
 
3.7%
33
 
2.8%
283
 
2.8%
142
 
1.9%
212
 
1.9%
92
 
1.9%
172
 
1.9%
Other values (35)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
111
 
10.3%
26
 
5.6%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
3401
0.9%
3371
0.9%
2061
0.9%
2041
0.9%
2031
0.9%

CGD GAILLAC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean26.59223301
Minimum0
Maximum295
Zeros34
Zeros (%)31.8%
Memory size984.0 B
2021-02-18T22:39:31.712758image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q324.5
95-th percentile161.7
Maximum295
Range295
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation52.73378143
Coefficient of variation (CV)1.983052022
Kurtosis9.422853675
Mean26.59223301
Median Absolute Deviation (MAD)3
Skewness2.966942878
Sum2739
Variance2780.851704
MonotocityNot monotonic
2021-02-18T22:39:31.815081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
034
31.8%
29
 
8.4%
18
 
7.5%
123
 
2.8%
33
 
2.8%
132
 
1.9%
162
 
1.9%
52
 
1.9%
112
 
1.9%
72
 
1.9%
Other values (36)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
034
31.8%
18
 
7.5%
29
 
8.4%
33
 
2.8%
52
 
1.9%
ValueCountFrequency (%)
2951
0.9%
2191
0.9%
2031
0.9%
1841
0.9%
1831
0.9%

CGD CASTELSARRASIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct35
Distinct (%)34.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.63106796
Minimum0
Maximum368
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:31.917418image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q319
95-th percentile94.9
Maximum368
Range368
Interquartile range (IQR)19

Descriptive statistics

Standard deviation46.13109842
Coefficient of variation (CV)2.236001476
Kurtosis31.89281268
Mean20.63106796
Median Absolute Deviation (MAD)2
Skewness4.868705736
Sum2125
Variance2128.078241
MonotocityNot monotonic
2021-02-18T22:39:32.014370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
035
32.7%
111
 
10.3%
27
 
6.5%
134
 
3.7%
34
 
3.7%
194
 
3.7%
383
 
2.8%
93
 
2.8%
122
 
1.9%
42
 
1.9%
Other values (25)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
111
 
10.3%
27
 
6.5%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
3681
0.9%
1631
0.9%
1051
0.9%
1041
0.9%
981
0.9%

CGD MONTAUBAN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean31.33980583
Minimum0
Maximum463
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:32.121279image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q320.5
95-th percentile166.7
Maximum463
Range463
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation66.19320405
Coefficient of variation (CV)2.112112769
Kurtosis19.16631803
Mean31.33980583
Median Absolute Deviation (MAD)7
Skewness3.858839751
Sum3228
Variance4381.540263
MonotocityNot monotonic
2021-02-18T22:39:32.226368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
031
29.0%
17
 
6.5%
26
 
5.6%
74
 
3.7%
123
 
2.8%
153
 
2.8%
133
 
2.8%
93
 
2.8%
732
 
1.9%
32
 
1.9%
Other values (36)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
17
 
6.5%
26
 
5.6%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
4631
0.9%
2831
0.9%
1911
0.9%
1821
0.9%
1781
0.9%

CGD BRIGNOLES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean47.03883495
Minimum0
Maximum550
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:32.330662image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q336
95-th percentile270.8
Maximum550
Range550
Interquartile range (IQR)36

Descriptive statistics

Standard deviation97.55078339
Coefficient of variation (CV)2.073835024
Kurtosis12.04429071
Mean47.03883495
Median Absolute Deviation (MAD)7
Skewness3.29313728
Sum4845
Variance9516.15534
MonotocityNot monotonic
2021-02-18T22:39:32.447941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
027
25.2%
17
 
6.5%
55
 
4.7%
154
 
3.7%
64
 
3.7%
33
 
2.8%
23
 
2.8%
2812
 
1.9%
42
 
1.9%
342
 
1.9%
Other values (37)44
41.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
17
 
6.5%
23
 
2.8%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
5501
0.9%
5201
0.9%
3091
0.9%
2812
1.9%
2711
0.9%

CGD DRAGUIGNAN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct54
Distinct (%)52.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean50.94174757
Minimum0
Maximum612
Zeros21
Zeros (%)19.6%
Memory size984.0 B
2021-02-18T22:39:32.589014image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median11
Q343.5
95-th percentile268.8
Maximum612
Range612
Interquartile range (IQR)42.5

Descriptive statistics

Standard deviation102.4093885
Coefficient of variation (CV)2.010323425
Kurtosis13.39367917
Mean50.94174757
Median Absolute Deviation (MAD)11
Skewness3.414251568
Sum5247
Variance10487.68285
MonotocityNot monotonic
2021-02-18T22:39:32.727249image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
021
19.6%
18
 
7.5%
25
 
4.7%
65
 
4.7%
44
 
3.7%
113
 
2.8%
243
 
2.8%
82
 
1.9%
262
 
1.9%
32
 
1.9%
Other values (44)48
44.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
021
19.6%
18
 
7.5%
25
 
4.7%
32
 
1.9%
44
 
3.7%
ValueCountFrequency (%)
6121
0.9%
5361
0.9%
3491
0.9%
2891
0.9%
2831
0.9%

CGD GASSIN ST TROPEZ
Real number (ℝ≥0)

MISSING
ZEROS

Distinct56
Distinct (%)54.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean59.57281553
Minimum0
Maximum839
Zeros22
Zeros (%)20.6%
Memory size984.0 B
2021-02-18T22:39:32.856570image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q353
95-th percentile253.4
Maximum839
Range839
Interquartile range (IQR)52

Descriptive statistics

Standard deviation126.8040485
Coefficient of variation (CV)2.128555572
Kurtosis16.30692762
Mean59.57281553
Median Absolute Deviation (MAD)9
Skewness3.679594173
Sum6136
Variance16079.2667
MonotocityNot monotonic
2021-02-18T22:39:32.963281image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
022
20.6%
17
 
6.5%
56
 
5.6%
34
 
3.7%
24
 
3.7%
63
 
2.8%
123
 
2.8%
142
 
1.9%
482
 
1.9%
72
 
1.9%
Other values (46)48
44.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
022
20.6%
17
 
6.5%
24
 
3.7%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
8391
0.9%
5411
0.9%
4521
0.9%
4411
0.9%
3651
0.9%

CGD HYERES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct52
Distinct (%)50.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean44.58252427
Minimum0
Maximum502
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:39:33.069335image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q343
95-th percentile265.1
Maximum502
Range502
Interquartile range (IQR)42

Descriptive statistics

Standard deviation87.65378914
Coefficient of variation (CV)1.966101978
Kurtosis10.36678562
Mean44.58252427
Median Absolute Deviation (MAD)8
Skewness3.08670165
Sum4592
Variance7683.18675
MonotocityNot monotonic
2021-02-18T22:39:33.182696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
025
23.4%
17
 
6.5%
34
 
3.7%
24
 
3.7%
64
 
3.7%
44
 
3.7%
123
 
2.8%
172
 
1.9%
102
 
1.9%
432
 
1.9%
Other values (42)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
17
 
6.5%
24
 
3.7%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
5021
0.9%
3991
0.9%
3221
0.9%
2821
0.9%
2781
0.9%

CGD LA VALETTE DU VAR
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.23300971
Minimum0
Maximum206
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:39:33.287219image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median3
Q317.5
95-th percentile145
Maximum206
Range206
Interquartile range (IQR)17

Descriptive statistics

Standard deviation42.52201365
Coefficient of variation (CV)2.101615838
Kurtosis8.800972203
Mean20.23300971
Median Absolute Deviation (MAD)3
Skewness3.037753904
Sum2084
Variance1808.121645
MonotocityNot monotonic
2021-02-18T22:39:33.381380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
026
24.3%
113
12.1%
38
 
7.5%
67
 
6.5%
25
 
4.7%
43
 
2.8%
53
 
2.8%
103
 
2.8%
182
 
1.9%
172
 
1.9%
Other values (26)31
29.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
113
12.1%
25
 
4.7%
38
 
7.5%
43
 
2.8%
ValueCountFrequency (%)
2061
0.9%
1871
0.9%
1771
0.9%
1661
0.9%
1581
0.9%

CGD AVIGNON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean43.21359223
Minimum0
Maximum482
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:39:33.482520image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q335.5
95-th percentile283.1
Maximum482
Range482
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation88.47206832
Coefficient of variation (CV)2.047320386
Kurtosis8.850571766
Mean43.21359223
Median Absolute Deviation (MAD)6
Skewness2.941664592
Sum4451
Variance7827.306872
MonotocityNot monotonic
2021-02-18T22:39:33.594066image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
025
23.4%
18
 
7.5%
46
 
5.6%
26
 
5.6%
35
 
4.7%
134
 
3.7%
173
 
2.8%
62
 
1.9%
92
 
1.9%
152
 
1.9%
Other values (39)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
18
 
7.5%
26
 
5.6%
35
 
4.7%
46
 
5.6%
ValueCountFrequency (%)
4821
0.9%
3461
0.9%
3371
0.9%
3221
0.9%
3151
0.9%

CGD CARPENTRAS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.93203883
Minimum0
Maximum323
Zeros32
Zeros (%)29.9%
Memory size984.0 B
2021-02-18T22:39:33.697643image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q315
95-th percentile148.2
Maximum323
Range323
Interquartile range (IQR)15

Descriptive statistics

Standard deviation50.85586363
Coefficient of variation (CV)2.217677372
Kurtosis14.25877219
Mean22.93203883
Median Absolute Deviation (MAD)3
Skewness3.530031366
Sum2362
Variance2586.318865
MonotocityNot monotonic
2021-02-18T22:39:33.795918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
032
29.9%
114
13.1%
25
 
4.7%
104
 
3.7%
53
 
2.8%
133
 
2.8%
152
 
1.9%
492
 
1.9%
42
 
1.9%
112
 
1.9%
Other values (29)34
31.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
032
29.9%
114
13.1%
25
 
4.7%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
3231
0.9%
1941
0.9%
1831
0.9%
1791
0.9%
1761
0.9%

CGD ORANGE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean25.7184466
Minimum0
Maximum281
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:33.896152image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q323
95-th percentile149
Maximum281
Range281
Interquartile range (IQR)23

Descriptive statistics

Standard deviation53.07678815
Coefficient of variation (CV)2.063763375
Kurtosis9.442280127
Mean25.7184466
Median Absolute Deviation (MAD)3
Skewness3.013270365
Sum2649
Variance2817.145441
MonotocityNot monotonic
2021-02-18T22:39:33.988622image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
031
29.0%
18
 
7.5%
37
 
6.5%
27
 
6.5%
76
 
5.6%
105
 
4.7%
43
 
2.8%
202
 
1.9%
82
 
1.9%
282
 
1.9%
Other values (27)30
28.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
18
 
7.5%
27
 
6.5%
37
 
6.5%
43
 
2.8%
ValueCountFrequency (%)
2811
0.9%
2561
0.9%
1971
0.9%
1911
0.9%
1591
0.9%

CGD PERTUIS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean37.29126214
Minimum0
Maximum414
Zeros29
Zeros (%)27.1%
Memory size984.0 B
2021-02-18T22:39:34.094884image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q334.5
95-th percentile251
Maximum414
Range414
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation74.93979689
Coefficient of variation (CV)2.009580599
Kurtosis8.694452405
Mean37.29126214
Median Absolute Deviation (MAD)5
Skewness2.898799802
Sum3841
Variance5615.973158
MonotocityNot monotonic
2021-02-18T22:39:34.197831image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
029
27.1%
210
 
9.3%
18
 
7.5%
144
 
3.7%
122
 
1.9%
42
 
1.9%
262
 
1.9%
72
 
1.9%
62
 
1.9%
212
 
1.9%
Other values (38)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
029
27.1%
18
 
7.5%
210
 
9.3%
32
 
1.9%
42
 
1.9%
ValueCountFrequency (%)
4141
0.9%
2821
0.9%
2681
0.9%
2611
0.9%
2551
0.9%

CGD FONTENAY LE COMTE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean36.83495146
Minimum0
Maximum465
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:39:34.301591image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q339
95-th percentile190.7
Maximum465
Range465
Interquartile range (IQR)39

Descriptive statistics

Standard deviation72.5184354
Coefficient of variation (CV)1.968739812
Kurtosis13.86414796
Mean36.83495146
Median Absolute Deviation (MAD)6
Skewness3.35139389
Sum3794
Variance5258.923472
MonotocityNot monotonic
2021-02-18T22:39:34.408002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
028
26.2%
19
 
8.4%
26
 
5.6%
44
 
3.7%
114
 
3.7%
64
 
3.7%
202
 
1.9%
382
 
1.9%
102
 
1.9%
412
 
1.9%
Other values (39)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
19
 
8.4%
26
 
5.6%
31
 
0.9%
44
 
3.7%
ValueCountFrequency (%)
4651
0.9%
3281
0.9%
2221
0.9%
2021
0.9%
1991
0.9%

CGD LA ROCHE SUR YON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct53
Distinct (%)51.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean60.83495146
Minimum0
Maximum764
Zeros23
Zeros (%)21.5%
Memory size984.0 B
2021-02-18T22:39:34.516969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q345
95-th percentile313.5
Maximum764
Range764
Interquartile range (IQR)44

Descriptive statistics

Standard deviation120.0838022
Coefficient of variation (CV)1.973927805
Kurtosis13.05136869
Mean60.83495146
Median Absolute Deviation (MAD)9
Skewness3.255358081
Sum6266
Variance14420.11955
MonotocityNot monotonic
2021-02-18T22:39:34.629535image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
023
21.5%
112
 
11.2%
34
 
3.7%
53
 
2.8%
453
 
2.8%
153
 
2.8%
23
 
2.8%
372
 
1.9%
292
 
1.9%
72
 
1.9%
Other values (43)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
023
21.5%
112
11.2%
23
 
2.8%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
7641
0.9%
4781
0.9%
4631
0.9%
3471
0.9%
3191
0.9%

CGD LES SABLES D OLONNE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct51
Distinct (%)49.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean64.73786408
Minimum0
Maximum903
Zeros26
Zeros (%)24.3%
Memory size984.0 B
2021-02-18T22:39:36.906112image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median9
Q350.5
95-th percentile295.2
Maximum903
Range903
Interquartile range (IQR)50

Descriptive statistics

Standard deviation139.9589548
Coefficient of variation (CV)2.161933466
Kurtosis16.22254174
Mean64.73786408
Median Absolute Deviation (MAD)9
Skewness3.738249293
Sum6668
Variance19588.50904
MonotocityNot monotonic
2021-02-18T22:39:37.008939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
026
24.3%
17
 
6.5%
46
 
5.6%
24
 
3.7%
64
 
3.7%
93
 
2.8%
182
 
1.9%
902
 
1.9%
382
 
1.9%
282
 
1.9%
Other values (41)45
42.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
026
24.3%
17
 
6.5%
24
 
3.7%
46
 
5.6%
51
 
0.9%
ValueCountFrequency (%)
9031
0.9%
6551
0.9%
5171
0.9%
5091
0.9%
3801
0.9%

CGD CHATELLERAULT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.26213592
Minimum0
Maximum264
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:37.125739image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q323
95-th percentile84.7
Maximum264
Range264
Interquartile range (IQR)23

Descriptive statistics

Standard deviation38.09790308
Coefficient of variation (CV)1.880251086
Kurtosis17.28898085
Mean20.26213592
Median Absolute Deviation (MAD)2
Skewness3.565159466
Sum2087
Variance1451.450219
MonotocityNot monotonic
2021-02-18T22:39:37.248453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
035
32.7%
113
 
12.1%
24
 
3.7%
133
 
2.8%
33
 
2.8%
233
 
2.8%
223
 
2.8%
52
 
1.9%
92
 
1.9%
822
 
1.9%
Other values (28)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
113
 
12.1%
24
 
3.7%
33
 
2.8%
52
 
1.9%
ValueCountFrequency (%)
2641
0.9%
1611
0.9%
1081
0.9%
952
1.9%
851
0.9%

CGD MONTMORILLON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct37
Distinct (%)35.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean21.11650485
Minimum0
Maximum335
Zeros37
Zeros (%)34.6%
Memory size984.0 B
2021-02-18T22:39:37.348671image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q320
95-th percentile98.4
Maximum335
Range335
Interquartile range (IQR)20

Descriptive statistics

Standard deviation43.84135861
Coefficient of variation (CV)2.076165488
Kurtosis25.87705178
Mean21.11650485
Median Absolute Deviation (MAD)2
Skewness4.3184492
Sum2175
Variance1922.064725
MonotocityNot monotonic
2021-02-18T22:39:37.443172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
037
34.6%
111
 
10.3%
28
 
7.5%
164
 
3.7%
83
 
2.8%
33
 
2.8%
152
 
1.9%
182
 
1.9%
132
 
1.9%
302
 
1.9%
Other values (27)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
037
34.6%
111
 
10.3%
28
 
7.5%
33
 
2.8%
52
 
1.9%
ValueCountFrequency (%)
3351
0.9%
1471
0.9%
1251
0.9%
1111
0.9%
1021
0.9%

CGD POITIERS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean38.44660194
Minimum0
Maximum508
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:37.554986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q336.5
95-th percentile177
Maximum508
Range508
Interquartile range (IQR)36.5

Descriptive statistics

Standard deviation75.67224582
Coefficient of variation (CV)1.968242757
Kurtosis15.57360707
Mean38.44660194
Median Absolute Deviation (MAD)7
Skewness3.476410892
Sum3960
Variance5726.288787
MonotocityNot monotonic
2021-02-18T22:39:37.703902image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
030
28.0%
26
 
5.6%
15
 
4.7%
35
 
4.7%
253
 
2.8%
173
 
2.8%
402
 
1.9%
92
 
1.9%
42
 
1.9%
62
 
1.9%
Other values (40)43
40.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
15
 
4.7%
26
 
5.6%
35
 
4.7%
42
 
1.9%
ValueCountFrequency (%)
5081
0.9%
2961
0.9%
2621
0.9%
2361
0.9%
1881
0.9%

CGD BELLAC
Real number (ℝ≥0)

MISSING
ZEROS

Distinct33
Distinct (%)32.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean10.4368932
Minimum0
Maximum115
Zeros40
Zeros (%)37.4%
Memory size984.0 B
2021-02-18T22:39:37.827102image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q311
95-th percentile44.9
Maximum115
Range115
Interquartile range (IQR)11

Descriptive statistics

Standard deviation19.40268321
Coefficient of variation (CV)1.859047787
Kurtosis11.84761975
Mean10.4368932
Median Absolute Deviation (MAD)3
Skewness3.195347333
Sum1075
Variance376.4641157
MonotocityNot monotonic
2021-02-18T22:39:37.917854image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
040
37.4%
19
 
8.4%
36
 
5.6%
45
 
4.7%
104
 
3.7%
63
 
2.8%
212
 
1.9%
142
 
1.9%
262
 
1.9%
92
 
1.9%
Other values (23)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
040
37.4%
19
 
8.4%
21
 
0.9%
36
 
5.6%
45
 
4.7%
ValueCountFrequency (%)
1151
0.9%
871
0.9%
851
0.9%
711
0.9%
471
0.9%

CGD LIMOGES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct35
Distinct (%)34.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.38834951
Minimum0
Maximum282
Zeros35
Zeros (%)32.7%
Memory size984.0 B
2021-02-18T22:39:38.010951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q314
95-th percentile80.5
Maximum282
Range282
Interquartile range (IQR)14

Descriptive statistics

Standard deviation35.96055383
Coefficient of variation (CV)2.1942755
Kurtosis29.98804124
Mean16.38834951
Median Absolute Deviation (MAD)3
Skewness4.783297226
Sum1688
Variance1293.161432
MonotocityNot monotonic
2021-02-18T22:39:38.101605image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
035
32.7%
18
 
7.5%
36
 
5.6%
106
 
5.6%
26
 
5.6%
84
 
3.7%
113
 
2.8%
253
 
2.8%
142
 
1.9%
122
 
1.9%
Other values (25)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
035
32.7%
18
 
7.5%
26
 
5.6%
36
 
5.6%
41
 
0.9%
ValueCountFrequency (%)
2821
0.9%
1331
0.9%
1001
0.9%
981
0.9%
861
0.9%

CGD ST JUNIEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct38
Distinct (%)36.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.33009709
Minimum0
Maximum242
Zeros44
Zeros (%)41.1%
Memory size984.0 B
2021-02-18T22:39:38.196574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q316.5
95-th percentile75.5
Maximum242
Range242
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation34.3255431
Coefficient of variation (CV)2.101980344
Kurtosis19.41914846
Mean16.33009709
Median Absolute Deviation (MAD)2
Skewness3.865968476
Sum1682
Variance1178.242909
MonotocityNot monotonic
2021-02-18T22:39:38.297614image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
044
41.1%
17
 
6.5%
26
 
5.6%
94
 
3.7%
83
 
2.8%
112
 
1.9%
712
 
1.9%
212
 
1.9%
52
 
1.9%
432
 
1.9%
Other values (28)29
27.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
044
41.1%
17
 
6.5%
26
 
5.6%
31
 
0.9%
41
 
0.9%
ValueCountFrequency (%)
2421
0.9%
1341
0.9%
1121
0.9%
1091
0.9%
771
0.9%

CGD NEUFCHATEAU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean23.45631068
Minimum0
Maximum258
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:38.394414image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q322.5
95-th percentile106.8
Maximum258
Range258
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation43.74923567
Coefficient of variation (CV)1.865137117
Kurtosis9.731544492
Mean23.45631068
Median Absolute Deviation (MAD)4
Skewness2.875849865
Sum2416
Variance1913.995622
MonotocityNot monotonic
2021-02-18T22:39:38.496825image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
030
28.0%
110
 
9.3%
29
 
8.4%
55
 
4.7%
93
 
2.8%
213
 
2.8%
43
 
2.8%
133
 
2.8%
222
 
1.9%
322
 
1.9%
Other values (30)33
30.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
110
 
9.3%
29
 
8.4%
31
 
0.9%
43
 
2.8%
ValueCountFrequency (%)
2581
0.9%
1951
0.9%
1331
0.9%
1251
0.9%
1241
0.9%

CGD REMIREMONT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean30.29126214
Minimum0
Maximum355
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:39:38.597517image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q327.5
95-th percentile151.8
Maximum355
Range355
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation58.60546569
Coefficient of variation (CV)1.93473172
Kurtosis11.34538984
Mean30.29126214
Median Absolute Deviation (MAD)4
Skewness3.09653477
Sum3120
Variance3434.600609
MonotocityNot monotonic
2021-02-18T22:39:38.696734image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
028
26.2%
19
 
8.4%
26
 
5.6%
35
 
4.7%
174
 
3.7%
44
 
3.7%
133
 
2.8%
163
 
2.8%
53
 
2.8%
72
 
1.9%
Other values (33)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
19
 
8.4%
26
 
5.6%
35
 
4.7%
44
 
3.7%
ValueCountFrequency (%)
3551
0.9%
2671
0.9%
1831
0.9%
1781
0.9%
1591
0.9%

CGD ST DIE DES VOSGES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.74757282
Minimum0
Maximum405
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:38.804328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q325
95-th percentile132.7
Maximum405
Range405
Interquartile range (IQR)25

Descriptive statistics

Standard deviation58.29164647
Coefficient of variation (CV)2.10078362
Kurtosis19.51171255
Mean27.74757282
Median Absolute Deviation (MAD)3
Skewness3.915661778
Sum2858
Variance3397.916048
MonotocityNot monotonic
2021-02-18T22:39:38.910747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
030
28.0%
112
 
11.2%
37
 
6.5%
24
 
3.7%
163
 
2.8%
133
 
2.8%
92
 
1.9%
122
 
1.9%
72
 
1.9%
242
 
1.9%
Other values (34)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
112
 
11.2%
24
 
3.7%
37
 
6.5%
42
 
1.9%
ValueCountFrequency (%)
4051
0.9%
2761
0.9%
1501
0.9%
1421
0.9%
1371
0.9%

CGD AUXERRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean36.30097087
Minimum0
Maximum546
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:39.019181image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q332
95-th percentile172.1
Maximum546
Range546
Interquartile range (IQR)32

Descriptive statistics

Standard deviation76.67730126
Coefficient of variation (CV)2.112265854
Kurtosis20.37746526
Mean36.30097087
Median Absolute Deviation (MAD)4
Skewness3.955025648
Sum3739
Variance5879.408528
MonotocityNot monotonic
2021-02-18T22:39:39.116118image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
031
29.0%
18
 
7.5%
38
 
7.5%
23
 
2.8%
173
 
2.8%
193
 
2.8%
43
 
2.8%
252
 
1.9%
382
 
1.9%
52
 
1.9%
Other values (34)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
18
 
7.5%
23
 
2.8%
38
 
7.5%
43
 
2.8%
ValueCountFrequency (%)
5461
0.9%
2971
0.9%
2871
0.9%
1861
0.9%
1791
0.9%

CGD AVALLON
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean19.66019417
Minimum0
Maximum276
Zeros31
Zeros (%)29.0%
Memory size984.0 B
2021-02-18T22:39:39.217205image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q321
95-th percentile88.9
Maximum276
Range276
Interquartile range (IQR)21

Descriptive statistics

Standard deviation39.10432337
Coefficient of variation (CV)1.989010028
Kurtosis20.44152396
Mean19.66019417
Median Absolute Deviation (MAD)4
Skewness3.994956784
Sum2025
Variance1529.148106
MonotocityNot monotonic
2021-02-18T22:39:39.312420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
031
29.0%
110
 
9.3%
27
 
6.5%
84
 
3.7%
44
 
3.7%
422
 
1.9%
112
 
1.9%
262
 
1.9%
132
 
1.9%
212
 
1.9%
Other values (33)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
031
29.0%
110
 
9.3%
27
 
6.5%
31
 
0.9%
44
 
3.7%
ValueCountFrequency (%)
2761
0.9%
1841
0.9%
1211
0.9%
1001
0.9%
981
0.9%

CGD SENS
Real number (ℝ≥0)

MISSING
ZEROS

Distinct49
Distinct (%)47.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean46.82524272
Minimum0
Maximum527
Zeros19
Zeros (%)17.8%
Memory size984.0 B
2021-02-18T22:39:39.414381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q348.5
95-th percentile194.7
Maximum527
Range527
Interquartile range (IQR)47.5

Descriptive statistics

Standard deviation88.46184812
Coefficient of variation (CV)1.889191448
Kurtosis10.41721798
Mean46.82524272
Median Absolute Deviation (MAD)7
Skewness2.97667319
Sum4823
Variance7825.498572
MonotocityNot monotonic
2021-02-18T22:39:39.524228image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
019
17.8%
113
 
12.1%
26
 
5.6%
65
 
4.7%
43
 
2.8%
143
 
2.8%
93
 
2.8%
642
 
1.9%
52
 
1.9%
102
 
1.9%
Other values (39)45
42.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
019
17.8%
113
12.1%
26
 
5.6%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
5271
0.9%
3691
0.9%
3371
0.9%
2871
0.9%
2801
0.9%

CGD ETAMPES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean33.88349515
Minimum0
Maximum333
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:39:39.631344image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q327
95-th percentile186.2
Maximum333
Range333
Interquartile range (IQR)26

Descriptive statistics

Standard deviation65.26827007
Coefficient of variation (CV)1.926255535
Kurtosis7.754476344
Mean33.88349515
Median Absolute Deviation (MAD)6
Skewness2.786957231
Sum3490
Variance4259.947078
MonotocityNot monotonic
2021-02-18T22:39:39.760079image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
024
22.4%
113
 
12.1%
45
 
4.7%
194
 
3.7%
23
 
2.8%
133
 
2.8%
233
 
2.8%
33
 
2.8%
112
 
1.9%
122
 
1.9%
Other values (35)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
113
12.1%
23
 
2.8%
33
 
2.8%
45
 
4.7%
ValueCountFrequency (%)
3331
0.9%
2941
0.9%
2671
0.9%
2071
0.9%
1991
0.9%

CGD EVRY COURCOURONNES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct52
Distinct (%)50.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean54.21359223
Minimum0
Maximum450
Zeros20
Zeros (%)18.7%
Memory size984.0 B
2021-02-18T22:39:39.905820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.5
median8
Q348.5
95-th percentile317.3
Maximum450
Range450
Interquartile range (IQR)47

Descriptive statistics

Standard deviation100.612794
Coefficient of variation (CV)1.855859202
Kurtosis5.811498301
Mean54.21359223
Median Absolute Deviation (MAD)8
Skewness2.504637011
Sum5584
Variance10122.93432
MonotocityNot monotonic
2021-02-18T22:39:40.027490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
020
18.7%
211
 
10.3%
16
 
5.6%
84
 
3.7%
34
 
3.7%
54
 
3.7%
163
 
2.8%
252
 
1.9%
322
 
1.9%
232
 
1.9%
Other values (42)45
42.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
020
18.7%
16
 
5.6%
211
10.3%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
4501
0.9%
4381
0.9%
4181
0.9%
3291
0.9%
3211
0.9%

CGD PALAISEAU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean49.98058252
Minimum0
Maximum484
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:39:40.134244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q331
95-th percentile300.9
Maximum484
Range484
Interquartile range (IQR)30

Descriptive statistics

Standard deviation99.05910105
Coefficient of variation (CV)1.981951711
Kurtosis6.961469952
Mean49.98058252
Median Absolute Deviation (MAD)8
Skewness2.685442047
Sum5148
Variance9812.705502
MonotocityNot monotonic
2021-02-18T22:39:40.275348image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
024
22.4%
17
 
6.5%
36
 
5.6%
25
 
4.7%
303
 
2.8%
73
 
2.8%
153
 
2.8%
42
 
1.9%
282
 
1.9%
252
 
1.9%
Other values (40)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
17
 
6.5%
25
 
4.7%
36
 
5.6%
42
 
1.9%
ValueCountFrequency (%)
4841
0.9%
4581
0.9%
3351
0.9%
3311
0.9%
3221
0.9%

CGD L ISLE ADAM
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean45.37864078
Minimum0
Maximum383
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:39:40.388117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q341.5
95-th percentile275
Maximum383
Range383
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation86.52440623
Coefficient of variation (CV)1.906720976
Kurtosis5.988254982
Mean45.37864078
Median Absolute Deviation (MAD)7
Skewness2.572289091
Sum4674
Variance7486.472873
MonotocityNot monotonic
2021-02-18T22:39:40.496747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
025
23.4%
110
 
9.3%
25
 
4.7%
45
 
4.7%
274
 
3.7%
73
 
2.8%
243
 
2.8%
32
 
1.9%
102
 
1.9%
122
 
1.9%
Other values (38)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
110
 
9.3%
25
 
4.7%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
3831
0.9%
3801
0.9%
3511
0.9%
2971
0.9%
2781
0.9%

CGD MONTMORENCY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct53
Distinct (%)51.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean51.81553398
Minimum0
Maximum488
Zeros21
Zeros (%)19.6%
Memory size984.0 B
2021-02-18T22:39:40.625578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10
Q343.5
95-th percentile294.3
Maximum488
Range488
Interquartile range (IQR)42.5

Descriptive statistics

Standard deviation99.90640204
Coefficient of variation (CV)1.928116809
Kurtosis6.965975266
Mean51.81553398
Median Absolute Deviation (MAD)10
Skewness2.690909313
Sum5337
Variance9981.289168
MonotocityNot monotonic
2021-02-18T22:39:40.759816image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
021
19.6%
17
 
6.5%
24
 
3.7%
74
 
3.7%
34
 
3.7%
113
 
2.8%
53
 
2.8%
63
 
2.8%
303
 
2.8%
92
 
1.9%
Other values (43)49
45.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
021
19.6%
17
 
6.5%
24
 
3.7%
34
 
3.7%
42
 
1.9%
ValueCountFrequency (%)
4881
0.9%
4451
0.9%
3781
0.9%
3671
0.9%
3351
0.9%

CGD PONTOISE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)41.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean31.52427184
Minimum0
Maximum318
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:40.868003image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q327
95-th percentile164.3
Maximum318
Range318
Interquartile range (IQR)27

Descriptive statistics

Standard deviation63.59427842
Coefficient of variation (CV)2.017311573
Kurtosis8.720876044
Mean31.52427184
Median Absolute Deviation (MAD)4
Skewness2.946329062
Sum3247
Variance4044.232248
MonotocityNot monotonic
2021-02-18T22:39:40.980682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
030
28.0%
113
 
12.1%
205
 
4.7%
34
 
3.7%
24
 
3.7%
123
 
2.8%
43
 
2.8%
182
 
1.9%
92
 
1.9%
152
 
1.9%
Other values (33)35
32.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
113
12.1%
24
 
3.7%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
3181
0.9%
2821
0.9%
2751
0.9%
2631
0.9%
1901
0.9%

CGD LE MOULE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct51
Distinct (%)49.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean46.85436893
Minimum0
Maximum615
Zeros19
Zeros (%)17.8%
Memory size984.0 B
2021-02-18T22:39:41.086736image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median10
Q332
95-th percentile304.8
Maximum615
Range615
Interquartile range (IQR)30

Descriptive statistics

Standard deviation100.9971275
Coefficient of variation (CV)2.155554109
Kurtosis12.38493391
Mean46.85436893
Median Absolute Deviation (MAD)10
Skewness3.359581002
Sum4826
Variance10200.41976
MonotocityNot monotonic
2021-02-18T22:39:41.192296image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
019
17.8%
211
 
10.3%
37
 
6.5%
45
 
4.7%
323
 
2.8%
133
 
2.8%
63
 
2.8%
172
 
1.9%
102
 
1.9%
112
 
1.9%
Other values (41)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
019
17.8%
12
 
1.9%
211
10.3%
37
 
6.5%
45
 
4.7%
ValueCountFrequency (%)
6151
0.9%
4231
0.9%
3471
0.9%
3331
0.9%
3231
0.9%

CGD POINTE A PITRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean44.42718447
Minimum0
Maximum597
Zeros16
Zeros (%)15.0%
Memory size984.0 B
2021-02-18T22:39:41.301579image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median9
Q332.5
95-th percentile260.7
Maximum597
Range597
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation91.43631684
Coefficient of variation (CV)2.058116398
Kurtosis14.52633814
Mean44.42718447
Median Absolute Deviation (MAD)9
Skewness3.45984297
Sum4576
Variance8360.600038
MonotocityNot monotonic
2021-02-18T22:39:41.405432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
016
 
15.0%
211
 
10.3%
18
 
7.5%
56
 
5.6%
35
 
4.7%
43
 
2.8%
223
 
2.8%
123
 
2.8%
193
 
2.8%
113
 
2.8%
Other values (37)42
39.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
016
15.0%
18
7.5%
211
10.3%
35
 
4.7%
43
 
2.8%
ValueCountFrequency (%)
5971
0.9%
3531
0.9%
3051
0.9%
2991
0.9%
2781
0.9%

CGD ST CLAUDE (971)
Real number (ℝ≥0)

MISSING
ZEROS

Distinct39
Distinct (%)37.9%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean28.18446602
Minimum0
Maximum460
Zeros22
Zeros (%)20.6%
Memory size984.0 B
2021-02-18T22:39:41.509202image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q325
95-th percentile146.4
Maximum460
Range460
Interquartile range (IQR)24

Descriptive statistics

Standard deviation63.31399306
Coefficient of variation (CV)2.246414497
Kurtosis22.87810002
Mean28.18446602
Median Absolute Deviation (MAD)7
Skewness4.297973404
Sum2903
Variance4008.661717
MonotocityNot monotonic
2021-02-18T22:39:41.607665image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
022
20.6%
110
 
9.3%
27
 
6.5%
35
 
4.7%
94
 
3.7%
54
 
3.7%
83
 
2.8%
253
 
2.8%
353
 
2.8%
133
 
2.8%
Other values (29)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
022
20.6%
110
9.3%
27
 
6.5%
35
 
4.7%
42
 
1.9%
ValueCountFrequency (%)
4601
0.9%
2451
0.9%
2181
0.9%
2071
0.9%
1681
0.9%

CGD FORT DE FRANCE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct40
Distinct (%)38.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean22.76699029
Minimum0
Maximum356
Zeros25
Zeros (%)23.4%
Memory size984.0 B
2021-02-18T22:39:41.707621image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q319.5
95-th percentile114.1
Maximum356
Range356
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation50.29778069
Coefficient of variation (CV)2.20924154
Kurtosis20.68190717
Mean22.76699029
Median Absolute Deviation (MAD)4
Skewness4.089085141
Sum2345
Variance2529.866743
MonotocityNot monotonic
2021-02-18T22:39:41.807462image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
025
23.4%
115
14.0%
27
 
6.5%
114
 
3.7%
124
 
3.7%
43
 
2.8%
143
 
2.8%
32
 
1.9%
292
 
1.9%
62
 
1.9%
Other values (30)36
33.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
025
23.4%
115
14.0%
27
 
6.5%
32
 
1.9%
43
 
2.8%
ValueCountFrequency (%)
3561
0.9%
2041
0.9%
1801
0.9%
1511
0.9%
1311
0.9%

CGD LA TRINITE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct42
Distinct (%)40.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean24.4368932
Minimum0
Maximum335
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:41.913735image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q318.5
95-th percentile107.9
Maximum335
Range335
Interquartile range (IQR)18.5

Descriptive statistics

Standard deviation56.07202474
Coefficient of variation (CV)2.294564382
Kurtosis15.22016176
Mean24.4368932
Median Absolute Deviation (MAD)5
Skewness3.790687437
Sum2517
Variance3144.071959
MonotocityNot monotonic
2021-02-18T22:39:42.013661image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
027
25.2%
19
 
8.4%
45
 
4.7%
35
 
4.7%
25
 
4.7%
53
 
2.8%
233
 
2.8%
113
 
2.8%
133
 
2.8%
322
 
1.9%
Other values (32)38
35.5%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
19
 
8.4%
25
 
4.7%
35
 
4.7%
45
 
4.7%
ValueCountFrequency (%)
3351
0.9%
2611
0.9%
2511
0.9%
2381
0.9%
1131
0.9%

CGD LE MARIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct52
Distinct (%)50.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean41.13592233
Minimum0
Maximum665
Zeros20
Zeros (%)18.7%
Memory size984.0 B
2021-02-18T22:39:42.122660image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q331
95-th percentile204.6
Maximum665
Range665
Interquartile range (IQR)30

Descriptive statistics

Standard deviation90.21521637
Coefficient of variation (CV)2.19310061
Kurtosis23.6315662
Mean41.13592233
Median Absolute Deviation (MAD)9
Skewness4.303847793
Sum4237
Variance8138.785266
MonotocityNot monotonic
2021-02-18T22:39:42.227606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
020
18.7%
110
 
9.3%
29
 
8.4%
64
 
3.7%
263
 
2.8%
222
 
1.9%
72
 
1.9%
172
 
1.9%
312
 
1.9%
42
 
1.9%
Other values (42)47
43.9%
(Missing)4
 
3.7%
ValueCountFrequency (%)
020
18.7%
110
9.3%
29
8.4%
31
 
0.9%
42
 
1.9%
ValueCountFrequency (%)
6651
0.9%
3491
0.9%
2731
0.9%
2701
0.9%
2601
0.9%

CGD KOUROU
Real number (ℝ≥0)

MISSING
ZEROS

Distinct47
Distinct (%)45.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean30.39805825
Minimum0
Maximum487
Zeros23
Zeros (%)21.5%
Memory size984.0 B
2021-02-18T22:39:42.334976image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10
Q328
95-th percentile116.7
Maximum487
Range487
Interquartile range (IQR)27

Descriptive statistics

Standard deviation68.96210096
Coefficient of variation (CV)2.268635068
Kurtosis27.29674818
Mean30.39805825
Median Absolute Deviation (MAD)10
Skewness4.851130704
Sum3131
Variance4755.771369
MonotocityNot monotonic
2021-02-18T22:39:42.444226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
023
21.5%
19
 
8.4%
26
 
5.6%
64
 
3.7%
214
 
3.7%
33
 
2.8%
72
 
1.9%
202
 
1.9%
192
 
1.9%
352
 
1.9%
Other values (37)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
023
21.5%
19
 
8.4%
26
 
5.6%
33
 
2.8%
42
 
1.9%
ValueCountFrequency (%)
4871
0.9%
4131
0.9%
1941
0.9%
1411
0.9%
1361
0.9%

CGD MATOURY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct53
Distinct (%)51.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean37.73786408
Minimum0
Maximum589
Zeros15
Zeros (%)14.0%
Memory size984.0 B
2021-02-18T22:39:42.550699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median9
Q337.5
95-th percentile177.3
Maximum589
Range589
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation76.40000015
Coefficient of variation (CV)2.0244919
Kurtosis27.1610237
Mean37.73786408
Median Absolute Deviation (MAD)9
Skewness4.513047284
Sum3887
Variance5836.960023
MonotocityNot monotonic
2021-02-18T22:39:42.655691image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
015
 
14.0%
18
 
7.5%
35
 
4.7%
25
 
4.7%
44
 
3.7%
54
 
3.7%
63
 
2.8%
73
 
2.8%
83
 
2.8%
232
 
1.9%
Other values (43)51
47.7%
(Missing)4
 
3.7%
ValueCountFrequency (%)
015
14.0%
18
7.5%
25
 
4.7%
35
 
4.7%
44
 
3.7%
ValueCountFrequency (%)
5891
0.9%
2701
0.9%
2461
0.9%
1911
0.9%
1811
0.9%

CGD ST LAURENT DU MARONI
Real number (ℝ≥0)

MISSING
ZEROS

Distinct48
Distinct (%)46.6%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean33.61165049
Minimum0
Maximum571
Zeros22
Zeros (%)20.6%
Memory size984.0 B
2021-02-18T22:39:42.763593image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.5
median7
Q328
95-th percentile149.5
Maximum571
Range571
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation74.38706837
Coefficient of variation (CV)2.213133461
Kurtosis27.73658911
Mean33.61165049
Median Absolute Deviation (MAD)7
Skewness4.645500519
Sum3462
Variance5533.435941
MonotocityNot monotonic
2021-02-18T22:39:42.863231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
022
20.6%
67
 
6.5%
36
 
5.6%
24
 
3.7%
14
 
3.7%
73
 
2.8%
133
 
2.8%
53
 
2.8%
43
 
2.8%
192
 
1.9%
Other values (38)46
43.0%
(Missing)4
 
3.7%
ValueCountFrequency (%)
022
20.6%
14
 
3.7%
24
 
3.7%
36
 
5.6%
43
 
2.8%
ValueCountFrequency (%)
5711
0.9%
2711
0.9%
2431
0.9%
2221
0.9%
1701
0.9%

CGD ST BENOIT
Real number (ℝ≥0)

MISSING
ZEROS

Distinct44
Distinct (%)42.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean36.85436893
Minimum0
Maximum746
Zeros28
Zeros (%)26.2%
Memory size984.0 B
2021-02-18T22:39:42.968493image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q336
95-th percentile163.6
Maximum746
Range746
Interquartile range (IQR)36

Descriptive statistics

Standard deviation89.1573194
Coefficient of variation (CV)2.419179109
Kurtosis40.20333311
Mean36.85436893
Median Absolute Deviation (MAD)6
Skewness5.62503608
Sum3796
Variance7949.027603
MonotocityNot monotonic
2021-02-18T22:39:43.071430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
028
26.2%
17
 
6.5%
26
 
5.6%
35
 
4.7%
84
 
3.7%
284
 
3.7%
73
 
2.8%
53
 
2.8%
362
 
1.9%
182
 
1.9%
Other values (34)39
36.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
028
26.2%
17
 
6.5%
26
 
5.6%
35
 
4.7%
41
 
0.9%
ValueCountFrequency (%)
7461
0.9%
3261
0.9%
2131
0.9%
2101
0.9%
1931
0.9%

CGD ST PAUL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct50
Distinct (%)48.5%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean51.97087379
Minimum0
Maximum842
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:43.185218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q341
95-th percentile290.9
Maximum842
Range842
Interquartile range (IQR)41

Descriptive statistics

Standard deviation117.5114893
Coefficient of variation (CV)2.261102821
Kurtosis21.45819811
Mean51.97087379
Median Absolute Deviation (MAD)8
Skewness4.144131333
Sum5353
Variance13808.95012
MonotocityNot monotonic
2021-02-18T22:39:43.292368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
027
25.2%
17
 
6.5%
26
 
5.6%
54
 
3.7%
83
 
2.8%
103
 
2.8%
322
 
1.9%
392
 
1.9%
332
 
1.9%
512
 
1.9%
Other values (40)45
42.1%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
17
 
6.5%
26
 
5.6%
32
 
1.9%
41
 
0.9%
ValueCountFrequency (%)
8421
0.9%
4281
0.9%
4001
0.9%
3731
0.9%
3641
0.9%

CGD ST PIERRE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct59
Distinct (%)57.3%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean57.41747573
Minimum0
Maximum1045
Zeros24
Zeros (%)22.4%
Memory size984.0 B
2021-02-18T22:39:43.402192image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median10
Q353.5
95-th percentile269.3
Maximum1045
Range1045
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation135.0188458
Coefficient of variation (CV)2.351528765
Kurtosis29.91173513
Mean57.41747573
Median Absolute Deviation (MAD)10
Skewness4.889717748
Sum5914
Variance18230.08871
MonotocityNot monotonic
2021-02-18T22:39:43.513937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
024
22.4%
18
 
7.5%
24
 
3.7%
43
 
2.8%
73
 
2.8%
63
 
2.8%
33
 
2.8%
102
 
1.9%
52
 
1.9%
172
 
1.9%
Other values (49)49
45.8%
(Missing)4
 
3.7%
ValueCountFrequency (%)
024
22.4%
18
 
7.5%
24
 
3.7%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
10451
0.9%
5711
0.9%
4061
0.9%
3541
0.9%
3481
0.9%

CGD ST MARTIN ST BARTHELEMY
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)39.8%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean27.91262136
Minimum0
Maximum377
Zeros20
Zeros (%)18.7%
Memory size984.0 B
2021-02-18T22:39:43.619591image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q322
95-th percentile125
Maximum377
Range377
Interquartile range (IQR)21

Descriptive statistics

Standard deviation61.02267447
Coefficient of variation (CV)2.186203642
Kurtosis18.77861773
Mean27.91262136
Median Absolute Deviation (MAD)6
Skewness3.997320188
Sum2875
Variance3723.7668
MonotocityNot monotonic
2021-02-18T22:39:43.720694image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
020
18.7%
113
 
12.1%
26
 
5.6%
34
 
3.7%
74
 
3.7%
54
 
3.7%
114
 
3.7%
44
 
3.7%
94
 
3.7%
123
 
2.8%
Other values (31)37
34.6%
(Missing)4
 
3.7%
ValueCountFrequency (%)
020
18.7%
113
12.1%
26
 
5.6%
34
 
3.7%
44
 
3.7%
ValueCountFrequency (%)
3771
0.9%
3651
0.9%
1881
0.9%
1621
0.9%
1311
0.9%

CGD LES ARCHIPELS PAPEETE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct35
Distinct (%)34.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean20.83495146
Minimum0
Maximum410
Zeros38
Zeros (%)35.5%
Memory size984.0 B
2021-02-18T22:39:43.826059image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314.5
95-th percentile79.7
Maximum410
Range410
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation61.1613259
Coefficient of variation (CV)2.935515642
Kurtosis30.50739559
Mean20.83495146
Median Absolute Deviation (MAD)2
Skewness5.307871872
Sum2146
Variance3740.707786
MonotocityNot monotonic
2021-02-18T22:39:43.920585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
038
35.5%
28
 
7.5%
17
 
6.5%
155
 
4.7%
34
 
3.7%
84
 
3.7%
93
 
2.8%
73
 
2.8%
43
 
2.8%
142
 
1.9%
Other values (25)26
24.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
038
35.5%
17
 
6.5%
28
 
7.5%
34
 
3.7%
43
 
2.8%
ValueCountFrequency (%)
4101
0.9%
4011
0.9%
2111
0.9%
891
0.9%
841
0.9%

CGD LES ILES DU VENT FAAA
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)44.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean53.73786408
Minimum0
Maximum1108
Zeros30
Zeros (%)28.0%
Memory size984.0 B
2021-02-18T22:39:44.024883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q333
95-th percentile281
Maximum1108
Range1108
Interquartile range (IQR)33

Descriptive statistics

Standard deviation139.7353213
Coefficient of variation (CV)2.600314019
Kurtosis33.1519437
Mean53.73786408
Median Absolute Deviation (MAD)5
Skewness5.134367381
Sum5535
Variance19525.96002
MonotocityNot monotonic
2021-02-18T22:39:44.131022image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
030
28.0%
18
 
7.5%
26
 
5.6%
43
 
2.8%
213
 
2.8%
73
 
2.8%
33
 
2.8%
333
 
2.8%
162
 
1.9%
262
 
1.9%
Other values (36)40
37.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
030
28.0%
18
 
7.5%
26
 
5.6%
33
 
2.8%
43
 
2.8%
ValueCountFrequency (%)
11081
0.9%
5041
0.9%
4991
0.9%
3081
0.9%
2911
0.9%

CGD KONE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct31
Distinct (%)30.1%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean13.03883495
Minimum0
Maximum263
Zeros46
Zeros (%)43.0%
Memory size984.0 B
2021-02-18T22:39:44.229700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q312.5
95-th percentile61.7
Maximum263
Range263
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation31.85011538
Coefficient of variation (CV)2.442711753
Kurtosis37.84232373
Mean13.03883495
Median Absolute Deviation (MAD)1
Skewness5.409374625
Sum1343
Variance1014.42985
MonotocityNot monotonic
2021-02-18T22:39:44.331147image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
046
43.0%
110
 
9.3%
25
 
4.7%
44
 
3.7%
154
 
3.7%
302
 
1.9%
92
 
1.9%
82
 
1.9%
412
 
1.9%
372
 
1.9%
Other values (21)24
22.4%
(Missing)4
 
3.7%
ValueCountFrequency (%)
046
43.0%
110
 
9.3%
25
 
4.7%
44
 
3.7%
51
 
0.9%
ValueCountFrequency (%)
2631
0.9%
1001
0.9%
911
0.9%
841
0.9%
771
0.9%

CGD LA FOA
Real number (ℝ≥0)

MISSING
ZEROS

Distinct36
Distinct (%)35.0%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean16.48543689
Minimum0
Maximum292
Zeros44
Zeros (%)41.1%
Memory size984.0 B
2021-02-18T22:39:44.433013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q315.5
95-th percentile59.5
Maximum292
Range292
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation39.37448763
Coefficient of variation (CV)2.388440651
Kurtosis26.4023366
Mean16.48543689
Median Absolute Deviation (MAD)1
Skewness4.646444662
Sum1698
Variance1550.350276
MonotocityNot monotonic
2021-02-18T22:39:44.529702image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
044
41.1%
19
 
8.4%
25
 
4.7%
83
 
2.8%
113
 
2.8%
33
 
2.8%
132
 
1.9%
522
 
1.9%
392
 
1.9%
72
 
1.9%
Other values (26)28
26.2%
(Missing)4
 
3.7%
ValueCountFrequency (%)
044
41.1%
19
 
8.4%
25
 
4.7%
33
 
2.8%
41
 
0.9%
ValueCountFrequency (%)
2921
0.9%
1781
0.9%
1441
0.9%
1091
0.9%
851
0.9%

CGD NOUMEA
Real number (ℝ≥0)

MISSING
ZEROS

Distinct45
Distinct (%)43.7%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean49.85436893
Minimum0
Maximum1048
Zeros27
Zeros (%)25.2%
Memory size984.0 B
2021-02-18T22:39:44.650177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q340
95-th percentile210.9
Maximum1048
Range1048
Interquartile range (IQR)40

Descriptive statistics

Standard deviation126.9766389
Coefficient of variation (CV)2.546951082
Kurtosis38.53086924
Mean49.85436893
Median Absolute Deviation (MAD)6
Skewness5.528073799
Sum5135
Variance16123.06682
MonotocityNot monotonic
2021-02-18T22:39:44.792427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
027
25.2%
18
 
7.5%
25
 
4.7%
45
 
4.7%
65
 
4.7%
143
 
2.8%
213
 
2.8%
32
 
1.9%
1252
 
1.9%
232
 
1.9%
Other values (35)41
38.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
027
25.2%
18
 
7.5%
25
 
4.7%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
10481
0.9%
4481
0.9%
3811
0.9%
3461
0.9%
2181
0.9%

CGD POINDIMIE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct21
Distinct (%)20.4%
Missing4
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean7.427184466
Minimum0
Maximum181
Zeros49
Zeros (%)45.8%
Memory size984.0 B
2021-02-18T22:39:44.909850image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34.5
95-th percentile35.5
Maximum181
Range181
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation21.19406222
Coefficient of variation (CV)2.853579619
Kurtosis45.20560517
Mean7.427184466
Median Absolute Deviation (MAD)1
Skewness6.055674501
Sum765
Variance449.1882734
MonotocityNot monotonic
2021-02-18T22:39:44.994469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
049
45.8%
111
 
10.3%
210
 
9.3%
55
 
4.7%
45
 
4.7%
163
 
2.8%
173
 
2.8%
92
 
1.9%
32
 
1.9%
152
 
1.9%
Other values (11)11
 
10.3%
(Missing)4
 
3.7%
ValueCountFrequency (%)
049
45.8%
111
 
10.3%
210
 
9.3%
32
 
1.9%
45
 
4.7%
ValueCountFrequency (%)
1811
0.9%
671
0.9%
661
0.9%
471
0.9%
421
0.9%

Sample

First rows

Code indexLibellé index \ CGDCGD BELLEYCGD BOURG EN BRESSECGD GEXCGD TREVOUXCGD CHATEAU THIERRY NOGENTELCGD LAONCGD SOISSONSCGD ST QUENTINCGD VERVINSCGD MONTLUCONCGD MOULINSCGD VICHYCGD BARCELONNETTECGD CASTELLANECGD DIGNE LES BAINSCGD FORCALQUIERCGD BRIANCONCGD GAPCGD CANNESCGD GRASSECGD MENTONCGD NICECGD PUGET THENIERSCGD LARGENTIERECGD LE TEILCGD TOURNON SUR RHONECGD CHARLEVILLE MEZIERESCGD RETHELCGD REVINCGD SEDANCGD VOUZIERSCGD FOIXCGD PAMIERSCGD ST GIRONSCGD BAR SUR AUBECGD NOGENT SUR SEINECGD ROSIERES PRES TROYESCGD CARCASSONNECGD LIMOUXCGD NARBONNECGD MILLAUCGD RODEZCGD VILLEFRANCHE DE ROUERGUECGD AIX EN PROVENCECGD ARLESCGD AUBAGNECGD ISTRESCGD SALON DE PROVENCECGD BAYEUXCGD CAENCGD DEAUVILLECGD FALAISECGD LISIEUXCGD VIRE NORMANDIECGD AURILLACCGD MAURIACCGD ST FLOURCGD ANGOULEMECGD COGNACCGD CONFOLENSCGD JONZACCGD LA ROCHELLECGD ROCHEFORTCGD SAINTESCGD ST JEAN D ANGELYCGD BOURGESCGD ST AMAND MONTRONDCGD VIERZONCGD BRIVE LA GAILLARDECGD USSELCGD BEAUNECGD DIJONCGD IS SUR TILLECGD MONTBARDCGD DINANCGD GUINGAMPCGD LANNIONCGD ST BRIEUCCGD AUBUSSONCGD GUERETCGD BERGERACCGD NONTRONCGD PERIGUEUXCGD SARLAT LA CANEDACGD BESANCONCGD MONTBELIARDCGD PONTARLIERCGD CRESTCGD NYONSCGD PIERRELATTECGD ROMANS SUR ISERECGD BERNAYCGD EVREUXCGD LES ANDELYSCGD LOUVIERSCGD PONT AUDEMERCGD CHATEAUDUNCGD DREUXCGD LUCECGD NOGENT LE ROTROUCGD BRESTCGD CHATEAULINCGD LANDERNEAUCGD PLOURIN LES MORLAIXCGD QUIMPERCGD QUIMPERLECGD AJACCIOCGD PORTO VECCHIOCGD SARTENECGD BASTIACGD CALVICGD CORTECGD GHISONACCIACGD ALESCGD BAGNOLS SUR CEZECGD LE VIGANCGD NIMESCGD VAUVERTCGD MURETCGD ST GAUDENSCGD TOULOUSE MIRAILCGD TOULOUSE ST MICHELCGD VILLEFRANCHE DE LAURAGAISCGD AUCHCGD CONDOMCGD ARCACHONCGD BLAYECGD BOULIACCGD LANGON TOULENNECGD LESPARRE MEDOCCGD LIBOURNECGD MERIGNACCGD BEZIERSCGD CASTELNAU LE LEZCGD LODEVECGD LUNELCGD PEZENASCGD MONTFORT SUR MEUCGD REDONCGD RENNESCGD ST MALOCGD VITRECGD ISSOUDUNCGD LA CHATRECGD LE BLANCCGD AMBOISECGD CHINONCGD LOCHESCGD TOURSCGD BOURGOIN JALLIEUCGD GRENOBLECGD LA MURECGD LA TOUR DU PINCGD MEYLANCGD ST MARCELLINCGD VIENNECGD DOLECGD LONS LE SAUNIERCGD ST CLAUDECGD DAXCGD MONT DE MARSANCGD PARENTIS EN BORNCGD BLOISCGD ROMORANTIN LANTHENAYCGD VENDOMECGD MONTBRISONCGD ROANNECGD ST ETIENNECGD BRIOUDECGD LE PUY EN VELAYCGD YSSINGEAUXCGD ANCENIS ST GEREONCGD CHATEAUBRIANTCGD NANTESCGD PORNICCGD REZECGD ST NAZAIRECGD GIENCGD MONTARGISCGD ORLEANSCGD PITHIVIERSCGD CAHORSCGD FIGEACCGD GOURDONCGD AGENCGD MARMANDECGD VILLENEUVE SUR LOTCGD FLORAC TROIS RIVIERESCGD MENDECGD ANGERSCGD CHOLETCGD SAUMURCGD SEGRE EN ANJOU BLEUCGD AVRANCHESCGD CHERBOURG EN COTENTINCGD COUTANCESCGD ST LOCGD CHALONS EN CHAMPAGNECGD EPERNAYCGD REIMSCGD VITRY LE FRANCOISCGD CHAUMONTCGD LANGRESCGD ST DIZIERCGD CHATEAU GONTIER SUR MAYENNECGD MAYENNECGD LUNEVILLECGD NANCYCGD TOULCGD VAL DE BRIEYCGD COMMERCYCGD VERDUNCGD LORIENTCGD PLOERMELCGD PONTIVYCGD VANNESCGD BOULAY MOSELLECGD FORBACHCGD METZCGD SARREBOURGCGD SARREGUEMINESCGD THIONVILLECGD CHATEAU CHINON VILLECGD COSNE COURS SUR LOIRECGD NEVERSCGD AVESNES SUR HELPECGD CAMBRAICGD DOUAICGD DUNKERQUE HOYMILLECGD HAZEBROUCKCGD LILLECGD VALENCIENNESCGD BEAUVAISCGD CHANTILLYCGD CLERMONTCGD COMPIEGNECGD MERUCGD SENLISCGD ALENCON ARGENTANCGD DOMFRONT EN POIRAIECGD MORTAGNE AU PERCHECGD ARRASCGD BETHUNECGD CALAISCGD ECUIRESCGD ST OMERCGD ST POL SUR TERNOISECGD AMBERTCGD CLERMONT FERRANDCGD ISSOIRECGD RIOMCGD THIERSCGD BAYONNECGD OLORON STE MARIECGD ORTHEZCGD PAUCGD ARGELES GAZOSTCGD BAGNERES DE BIGORRECGD TARBESCGD CERETCGD PERPIGNANCGD PRADESCGD RIVESALTESCGD HAGUENAUCGD MOLSHEIMCGD SAVERNECGD SELESTATCGD STRASBOURGCGD WISSEMBOURGCGD ALTKIRCHCGD COLMARCGD MULHOUSECGD SOULTZ GUEBWILLERCGD BRONCGD GIVORSCGD L ARBRESLECGD LYONCGD VILLEFRANCHE SUR SAONECGD LURECGD VESOULCGD AUTUNCGD CHALON SUR SAONECGD CHAROLLESCGD LOUHANSCGD MACONCGD LA FLECHECGD LE MANSCGD MAMERSCGD ALBERTVILLECGD CHAMBERYCGD ST JEAN DE MAURIENNECGD ANNECYCGD BONNEVILLECGD CHAMONIX MONT BLANCCGD ST JULIEN EN GENEVOISCGD THONON LES BAINSCGD DIEPPECGD FECAMPCGD LE HAVRECGD NEUFCHATEL EN BRAYCGD ROUENCGD YVETOTCGD COULOMMIERSCGD FONTAINEBLEAUCGD MEAUXCGD MELUNCGD PROVINSCGD MANTES LA JOLIECGD RAMBOUILLETCGD ST GERMAIN EN LAYECGD BRESSUIRECGD NIORTCGD PARTHENAYCGD ABBEVILLECGD AMIENSCGD MONTDIDIERCGD PERONNECGD ALBICGD CASTRESCGD GAILLACCGD CASTELSARRASINCGD MONTAUBANCGD BRIGNOLESCGD DRAGUIGNANCGD GASSIN ST TROPEZCGD HYERESCGD LA VALETTE DU VARCGD AVIGNONCGD CARPENTRASCGD ORANGECGD PERTUISCGD FONTENAY LE COMTECGD LA ROCHE SUR YONCGD LES SABLES D OLONNECGD CHATELLERAULTCGD MONTMORILLONCGD POITIERSCGD BELLACCGD LIMOGESCGD ST JUNIENCGD NEUFCHATEAUCGD REMIREMONTCGD ST DIE DES VOSGESCGD AUXERRECGD AVALLONCGD SENSCGD ETAMPESCGD EVRY COURCOURONNESCGD PALAISEAUCGD L ISLE ADAMCGD MONTMORENCYCGD PONTOISECGD LE MOULECGD POINTE A PITRECGD ST CLAUDE (971)CGD FORT DE FRANCECGD LA TRINITECGD LE MARINCGD KOUROUCGD MATOURYCGD ST LAURENT DU MARONICGD ST BENOITCGD ST PAULCGD ST PIERRECGD ST MARTIN ST BARTHELEMYCGD LES ARCHIPELS PAPEETECGD LES ILES DU VENT FAAACGD KONECGD LA FOACGD NOUMEACGD POINDIMIE
01Règlements de compte entre malfaireurs0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.05.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.03.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.01.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.03.00.00.00.00.00.00.00.00.00.00.00.06.00.00.00.00.00.00.00.00.00.00.0
12Homicides pour voler et à l'occasion de vols0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.01.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.02.00.00.00.00.00.01.02.00.00.00.01.00.00.00.00.00.00.0
23Homicides pour d'autres motifs0.01.01.00.00.01.00.00.00.00.03.00.00.01.02.03.00.01.01.02.00.01.00.01.00.01.00.00.01.01.00.01.00.00.00.00.00.00.00.03.00.01.00.04.00.00.00.02.00.00.00.00.00.00.00.00.00.01.00.02.00.00.02.01.00.00.00.00.00.01.02.00.00.01.02.00.01.02.00.00.00.02.01.00.00.00.00.02.00.00.02.01.02.02.00.00.00.01.00.01.00.00.00.01.02.00.01.00.00.02.01.01.00.01.01.00.01.01.00.01.02.04.00.01.00.00.00.00.01.01.05.03.00.00.02.01.01.00.00.00.00.00.01.00.00.01.02.00.01.01.00.01.02.03.00.00.00.00.00.02.00.01.00.01.00.00.01.00.01.00.00.00.02.00.01.00.01.02.02.00.00.00.00.00.01.02.00.00.00.00.00.00.00.00.01.00.01.00.02.01.00.01.00.00.01.01.00.00.00.01.00.00.00.01.01.00.01.00.01.00.00.00.00.00.02.00.01.00.02.00.00.00.00.02.01.00.00.01.00.01.00.01.00.00.00.01.00.00.00.00.00.01.00.00.00.00.00.00.00.02.03.00.05.00.00.00.02.01.01.00.00.01.00.01.00.01.01.01.00.01.00.00.00.00.00.00.01.00.00.00.01.00.01.00.01.00.00.05.00.00.00.00.00.00.00.00.00.00.00.01.03.00.01.00.02.00.01.00.02.00.00.01.03.05.01.00.01.00.00.00.00.02.00.00.00.01.00.00.01.00.00.00.00.00.00.00.01.00.01.00.02.01.05.08.01.02.01.06.07.06.011.00.02.02.02.01.02.01.02.01.01.0
34Tentatives d'homicides pour voler et à l'occasion de vols0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.06.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.02.00.01.00.00.00.00.00.00.00.00.00.00.00.01.04.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.01.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.01.00.05.00.01.05.07.01.03.014.00.00.00.01.00.00.00.00.01.00.0
45Tentatives homicides pour d'autres motifs2.01.00.04.00.07.01.01.01.00.00.04.00.00.01.00.00.00.01.02.00.08.00.00.00.00.00.01.01.01.00.02.01.00.01.00.02.02.02.02.02.00.00.09.04.02.010.01.02.00.01.01.00.02.00.00.00.02.02.00.03.07.06.01.01.00.00.00.03.01.00.01.00.00.00.03.02.02.01.01.00.00.02.00.02.04.00.00.00.01.06.02.00.05.00.02.00.04.05.01.01.00.00.01.02.01.01.03.01.00.03.00.01.03.05.00.03.03.00.00.02.03.02.00.00.04.01.02.07.019.08.010.02.029.01.02.06.00.02.03.01.03.00.02.00.02.01.00.00.01.03.02.01.01.05.06.01.00.00.04.00.07.01.05.00.02.00.01.02.00.00.00.07.02.00.06.02.00.00.02.01.00.00.00.03.06.02.01.00.09.06.02.01.02.00.01.02.02.00.00.03.02.01.00.02.00.02.01.00.01.01.09.03.00.04.09.02.06.03.01.00.00.00.03.00.04.00.05.01.01.02.05.00.03.01.05.04.02.00.00.04.01.00.02.01.02.01.00.00.01.01.04.01.01.01.02.00.02.00.08.01.00.02.02.00.00.04.02.01.02.010.03.02.03.02.03.01.03.02.01.01.00.03.00.017.01.00.00.02.03.00.04.02.00.01.01.01.01.00.00.01.00.05.01.00.00.02.02.01.03.01.02.03.03.00.04.02.00.01.00.00.02.07.03.04.028.00.02.01.04.00.05.05.01.00.00.02.01.00.00.02.019.05.01.02.01.03.04.020.090.09.00.011.014.02.011.07.017.020.016.027.08.05.010.09.00.04.00.02.06.00.0
56Coups et blessures volontaires suivis de mort0.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.01.00.00.01.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.01.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.01.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.01.00.00.00.00.00.01.00.00.01.01.00.00.00.00.00.00.00.00.00.00.00.00.01.01.00.00.01.00.00.00.01.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.01.01.00.00.00.01.00.00.01.00.00.01.00.00.01.00.00.00.00.00.00.00.01.03.00.0
67Autres coups et blessures volontaires criminels ou correctionnels259.0301.0312.0391.0140.0323.0206.0212.0213.0113.089.0220.049.061.0160.0141.099.0153.0427.0225.096.0264.095.0180.0231.0261.00.0112.0173.0284.057.0140.0199.0102.0165.0240.0199.0256.0144.0313.086.0138.0139.0356.0351.0153.0188.0329.0178.0201.080.0175.0109.0154.0109.050.083.0174.0136.0223.0171.0201.0424.0229.0147.0113.0192.0129.0192.0105.0182.0267.0114.0211.0315.0249.0249.0465.075.0146.0124.0175.0176.0168.0248.0346.0208.0202.087.0166.0258.0230.0288.0279.0250.0278.0216.0192.0271.0170.0253.0214.0167.0227.0327.0209.0120.0163.052.0166.088.033.072.0346.0256.0101.0359.0350.0606.0158.0586.0516.0369.0195.0234.0357.0373.0301.0424.0333.0578.0394.0383.0520.0249.0419.0492.0273.0277.0559.0262.0484.0170.0183.091.0321.0187.0191.0196.0495.0360.0215.0393.0558.0307.0535.0165.0168.0167.0422.0132.0223.0107.0328.0111.0422.0158.0145.0135.0131.0133.0163.0326.0303.0337.0551.0422.0231.0147.0342.0274.097.0140.0106.0230.0395.0165.026.094.0286.0227.0300.0200.0266.0200.0121.0152.0144.0212.0154.0186.090.0106.0144.0308.0262.0188.0320.084.0158.0235.0198.0437.0269.0238.0359.0246.0202.0294.0190.0120.0334.070.0130.0185.0486.0626.0350.0191.0211.0315.0102.0268.0323.0299.0408.0394.0345.0212.0167.0234.0365.0204.0252.0278.0340.0238.056.0163.0165.0169.0166.0155.0120.0189.0168.042.0150.0121.0313.0380.0157.0343.0294.0261.0216.0332.0275.0118.0160.0235.0360.0399.0316.0371.0441.0270.0354.0297.0278.0111.0189.0164.0152.0153.0349.0464.0239.0328.0380.0168.0607.0490.0198.0314.0191.0189.0112.0123.0290.0243.0223.0359.0139.0357.0157.0122.0201.0191.0176.0181.0295.0190.0299.0249.0214.0373.097.0337.0219.0163.0283.0520.0536.0441.0322.0109.0337.0194.0256.0268.0328.0478.0517.0161.0125.0296.087.0133.0134.0195.0267.0276.0297.0184.0527.0294.0450.0331.0383.0378.0190.0615.0597.0460.0356.0335.0665.0487.0589.0571.0746.0842.01045.0365.0401.01108.0263.0292.01048.0181.0
78Prises d'otages à l'occasion de vols0.01.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.02.00.00.01.00.00.00.01.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.01.00.00.00.00.00.00.01.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.01.00.01.00.00.00.00.01.00.00.01.00.00.00.00.00.00.00.01.00.00.00.00.00.01.00.00.00.02.00.00.02.00.02.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.02.00.00.00.01.00.05.04.00.00.00.00.00.00.00.00.00.00.0
89Prises d'otages dans un autre but0.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.01.01.01.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.01.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.01.01.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.01.00.00.00.03.01.00.00.00.00.00.00.00.02.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.01.00.00.01.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.01.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.01.00.00.00.00.00.01.00.00.00.00.00.00.00.01.00.00.02.00.00.00.00.02.01.02.03.00.00.00.01.00.00.00.00.00.00.0
910Sequestrations4.02.010.06.02.02.02.00.00.00.00.04.00.02.01.01.01.00.03.04.01.01.01.01.02.02.00.00.01.03.00.00.05.01.01.01.01.00.01.02.00.02.01.06.00.05.02.03.03.00.01.03.00.04.01.00.00.00.00.01.03.01.03.03.01.00.01.00.01.01.04.05.00.00.05.01.00.08.00.02.01.00.03.00.02.04.02.02.02.02.02.02.03.06.01.02.03.02.02.03.04.01.01.03.04.01.01.01.00.03.00.00.03.01.03.00.03.03.04.01.07.08.06.01.02.02.06.03.03.06.09.06.03.07.04.02.03.02.04.07.04.02.00.02.00.00.00.00.03.08.07.03.02.011.02.09.02.02.02.03.02.01.01.05.00.05.01.00.01.01.01.04.02.02.03.08.00.02.00.01.05.03.02.01.00.01.02.00.01.04.06.04.04.00.01.01.00.00.00.03.03.00.00.02.03.03.01.03.00.02.00.00.05.02.03.03.03.04.02.02.01.06.02.00.02.00.01.02.00.00.03.01.02.04.08.02.07.08.01.00.04.02.00.00.03.00.01.00.01.02.01.01.02.00.06.00.00.01.02.04.08.02.01.05.01.01.03.02.00.03.03.05.04.06.04.04.01.03.02.01.01.00.00.00.01.03.03.01.01.05.00.09.06.03.03.03.01.01.02.02.03.03.011.01.05.02.00.01.03.00.02.01.04.00.01.02.02.01.05.02.00.04.06.06.09.01.00.02.01.00.02.04.08.04.01.02.07.00.03.02.01.00.00.01.01.05.05.08.07.04.010.02.02.02.05.01.03.01.06.08.014.03.07.03.04.01.00.00.00.07.00.0

Last rows

Code indexLibellé index \ CGDCGD BELLEYCGD BOURG EN BRESSECGD GEXCGD TREVOUXCGD CHATEAU THIERRY NOGENTELCGD LAONCGD SOISSONSCGD ST QUENTINCGD VERVINSCGD MONTLUCONCGD MOULINSCGD VICHYCGD BARCELONNETTECGD CASTELLANECGD DIGNE LES BAINSCGD FORCALQUIERCGD BRIANCONCGD GAPCGD CANNESCGD GRASSECGD MENTONCGD NICECGD PUGET THENIERSCGD LARGENTIERECGD LE TEILCGD TOURNON SUR RHONECGD CHARLEVILLE MEZIERESCGD RETHELCGD REVINCGD SEDANCGD VOUZIERSCGD FOIXCGD PAMIERSCGD ST GIRONSCGD BAR SUR AUBECGD NOGENT SUR SEINECGD ROSIERES PRES TROYESCGD CARCASSONNECGD LIMOUXCGD NARBONNECGD MILLAUCGD RODEZCGD VILLEFRANCHE DE ROUERGUECGD AIX EN PROVENCECGD ARLESCGD AUBAGNECGD ISTRESCGD SALON DE PROVENCECGD BAYEUXCGD CAENCGD DEAUVILLECGD FALAISECGD LISIEUXCGD VIRE NORMANDIECGD AURILLACCGD MAURIACCGD ST FLOURCGD ANGOULEMECGD COGNACCGD CONFOLENSCGD JONZACCGD LA ROCHELLECGD ROCHEFORTCGD SAINTESCGD ST JEAN D ANGELYCGD BOURGESCGD ST AMAND MONTRONDCGD VIERZONCGD BRIVE LA GAILLARDECGD USSELCGD BEAUNECGD DIJONCGD IS SUR TILLECGD MONTBARDCGD DINANCGD GUINGAMPCGD LANNIONCGD ST BRIEUCCGD AUBUSSONCGD GUERETCGD BERGERACCGD NONTRONCGD PERIGUEUXCGD SARLAT LA CANEDACGD BESANCONCGD MONTBELIARDCGD PONTARLIERCGD CRESTCGD NYONSCGD PIERRELATTECGD ROMANS SUR ISERECGD BERNAYCGD EVREUXCGD LES ANDELYSCGD LOUVIERSCGD PONT AUDEMERCGD CHATEAUDUNCGD DREUXCGD LUCECGD NOGENT LE ROTROUCGD BRESTCGD CHATEAULINCGD LANDERNEAUCGD PLOURIN LES MORLAIXCGD QUIMPERCGD QUIMPERLECGD AJACCIOCGD PORTO VECCHIOCGD SARTENECGD BASTIACGD CALVICGD CORTECGD GHISONACCIACGD ALESCGD BAGNOLS SUR CEZECGD LE VIGANCGD NIMESCGD VAUVERTCGD MURETCGD ST GAUDENSCGD TOULOUSE MIRAILCGD TOULOUSE ST MICHELCGD VILLEFRANCHE DE LAURAGAISCGD AUCHCGD CONDOMCGD ARCACHONCGD BLAYECGD BOULIACCGD LANGON TOULENNECGD LESPARRE MEDOCCGD LIBOURNECGD MERIGNACCGD BEZIERSCGD CASTELNAU LE LEZCGD LODEVECGD LUNELCGD PEZENASCGD MONTFORT SUR MEUCGD REDONCGD RENNESCGD ST MALOCGD VITRECGD ISSOUDUNCGD LA CHATRECGD LE BLANCCGD AMBOISECGD CHINONCGD LOCHESCGD TOURSCGD BOURGOIN JALLIEUCGD GRENOBLECGD LA MURECGD LA TOUR DU PINCGD MEYLANCGD ST MARCELLINCGD VIENNECGD DOLECGD LONS LE SAUNIERCGD ST CLAUDECGD DAXCGD MONT DE MARSANCGD PARENTIS EN BORNCGD BLOISCGD ROMORANTIN LANTHENAYCGD VENDOMECGD MONTBRISONCGD ROANNECGD ST ETIENNECGD BRIOUDECGD LE PUY EN VELAYCGD YSSINGEAUXCGD ANCENIS ST GEREONCGD CHATEAUBRIANTCGD NANTESCGD PORNICCGD REZECGD ST NAZAIRECGD GIENCGD MONTARGISCGD ORLEANSCGD PITHIVIERSCGD CAHORSCGD FIGEACCGD GOURDONCGD AGENCGD MARMANDECGD VILLENEUVE SUR LOTCGD FLORAC TROIS RIVIERESCGD MENDECGD ANGERSCGD CHOLETCGD SAUMURCGD SEGRE EN ANJOU BLEUCGD AVRANCHESCGD CHERBOURG EN COTENTINCGD COUTANCESCGD ST LOCGD CHALONS EN CHAMPAGNECGD EPERNAYCGD REIMSCGD VITRY LE FRANCOISCGD CHAUMONTCGD LANGRESCGD ST DIZIERCGD CHATEAU GONTIER SUR MAYENNECGD MAYENNECGD LUNEVILLECGD NANCYCGD TOULCGD VAL DE BRIEYCGD COMMERCYCGD VERDUNCGD LORIENTCGD PLOERMELCGD PONTIVYCGD VANNESCGD BOULAY MOSELLECGD FORBACHCGD METZCGD SARREBOURGCGD SARREGUEMINESCGD THIONVILLECGD CHATEAU CHINON VILLECGD COSNE COURS SUR LOIRECGD NEVERSCGD AVESNES SUR HELPECGD CAMBRAICGD DOUAICGD DUNKERQUE HOYMILLECGD HAZEBROUCKCGD LILLECGD VALENCIENNESCGD BEAUVAISCGD CHANTILLYCGD CLERMONTCGD COMPIEGNECGD MERUCGD SENLISCGD ALENCON ARGENTANCGD DOMFRONT EN POIRAIECGD MORTAGNE AU PERCHECGD ARRASCGD BETHUNECGD CALAISCGD ECUIRESCGD ST OMERCGD ST POL SUR TERNOISECGD AMBERTCGD CLERMONT FERRANDCGD ISSOIRECGD RIOMCGD THIERSCGD BAYONNECGD OLORON STE MARIECGD ORTHEZCGD PAUCGD ARGELES GAZOSTCGD BAGNERES DE BIGORRECGD TARBESCGD CERETCGD PERPIGNANCGD PRADESCGD RIVESALTESCGD HAGUENAUCGD MOLSHEIMCGD SAVERNECGD SELESTATCGD STRASBOURGCGD WISSEMBOURGCGD ALTKIRCHCGD COLMARCGD MULHOUSECGD SOULTZ GUEBWILLERCGD BRONCGD GIVORSCGD L ARBRESLECGD LYONCGD VILLEFRANCHE SUR SAONECGD LURECGD VESOULCGD AUTUNCGD CHALON SUR SAONECGD CHAROLLESCGD LOUHANSCGD MACONCGD LA FLECHECGD LE MANSCGD MAMERSCGD ALBERTVILLECGD CHAMBERYCGD ST JEAN DE MAURIENNECGD ANNECYCGD BONNEVILLECGD CHAMONIX MONT BLANCCGD ST JULIEN EN GENEVOISCGD THONON LES BAINSCGD DIEPPECGD FECAMPCGD LE HAVRECGD NEUFCHATEL EN BRAYCGD ROUENCGD YVETOTCGD COULOMMIERSCGD FONTAINEBLEAUCGD MEAUXCGD MELUNCGD PROVINSCGD MANTES LA JOLIECGD RAMBOUILLETCGD ST GERMAIN EN LAYECGD BRESSUIRECGD NIORTCGD PARTHENAYCGD ABBEVILLECGD AMIENSCGD MONTDIDIERCGD PERONNECGD ALBICGD CASTRESCGD GAILLACCGD CASTELSARRASINCGD MONTAUBANCGD BRIGNOLESCGD DRAGUIGNANCGD GASSIN ST TROPEZCGD HYERESCGD LA VALETTE DU VARCGD AVIGNONCGD CARPENTRASCGD ORANGECGD PERTUISCGD FONTENAY LE COMTECGD LA ROCHE SUR YONCGD LES SABLES D OLONNECGD CHATELLERAULTCGD MONTMORILLONCGD POITIERSCGD BELLACCGD LIMOGESCGD ST JUNIENCGD NEUFCHATEAUCGD REMIREMONTCGD ST DIE DES VOSGESCGD AUXERRECGD AVALLONCGD SENSCGD ETAMPESCGD EVRY COURCOURONNESCGD PALAISEAUCGD L ISLE ADAMCGD MONTMORENCYCGD PONTOISECGD LE MOULECGD POINTE A PITRECGD ST CLAUDE (971)CGD FORT DE FRANCECGD LA TRINITECGD LE MARINCGD KOUROUCGD MATOURYCGD ST LAURENT DU MARONICGD ST BENOITCGD ST PAULCGD ST PIERRECGD ST MARTIN ST BARTHELEMYCGD LES ARCHIPELS PAPEETECGD LES ILES DU VENT FAAACGD KONECGD LA FOACGD NOUMEACGD POINDIMIE
9798Banqueroutes, abus de biens sociaux et autres délits de société2.03.01.01.00.01.00.00.01.01.00.03.00.00.00.02.02.02.09.02.01.03.01.01.01.03.00.00.00.01.00.00.01.01.03.00.03.03.00.07.03.01.01.07.03.03.01.02.02.01.00.00.02.00.03.01.01.01.01.00.01.01.02.03.00.01.02.01.01.01.02.00.00.02.02.01.01.01.00.00.03.00.00.00.02.03.02.01.00.00.01.02.05.01.00.03.01.03.04.01.04.02.01.05.01.01.09.05.03.04.01.02.02.01.01.00.00.03.01.00.03.02.02.01.01.06.04.05.04.03.06.01.03.01.01.01.02.01.01.03.01.04.01.00.00.01.01.01.00.03.02.03.05.02.06.05.00.00.00.04.00.01.04.01.02.03.02.01.02.01.00.02.02.04.01.02.00.00.02.04.00.02.00.01.00.03.00.00.02.01.02.03.00.01.02.02.02.00.04.02.03.00.01.00.01.01.01.05.01.00.02.02.07.04.05.06.01.04.05.03.03.03.00.03.01.01.01.05.01.02.01.01.00.02.00.00.01.01.05.05.02.00.00.02.00.00.00.00.02.00.03.00.02.04.01.04.00.03.00.00.06.00.02.03.04.03.06.04.01.05.09.07.07.01.01.05.00.01.01.01.01.03.01.03.01.01.01.02.03.06.00.010.01.02.00.04.01.00.00.00.01.01.00.00.02.01.04.05.01.01.00.01.01.01.01.00.00.00.01.02.01.02.05.09.012.03.01.04.02.02.02.00.02.04.00.02.01.00.00.00.01.03.03.03.00.05.00.00.01.02.02.04.03.03.02.00.05.06.02.01.00.05.05.011.03.02.02.02.00.06.02.0
9899Index non utiliséNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
99100Index non utiliséNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
100101Prix illicittes, publicité fausse et infractions aux règles de la concurrence0.02.00.02.02.01.00.00.01.00.02.00.00.00.01.00.00.01.04.02.01.01.06.02.01.01.00.00.01.00.00.00.01.01.02.02.01.01.00.00.00.02.00.01.01.01.00.04.02.00.01.01.00.01.02.00.01.02.04.02.03.02.02.01.01.00.01.00.03.02.01.00.01.00.01.00.02.01.06.00.00.00.03.00.00.05.00.01.00.00.02.00.01.00.00.00.01.03.01.00.03.00.01.01.01.01.00.01.00.00.01.00.02.01.01.00.01.03.02.01.04.00.02.00.01.03.02.02.02.05.02.02.01.04.00.01.00.02.03.01.00.01.00.01.00.01.00.01.00.01.00.01.00.03.02.00.00.00.02.02.01.00.02.01.00.00.01.00.01.02.02.00.01.00.02.04.02.00.00.02.01.00.02.00.01.00.00.00.00.01.03.02.03.01.01.02.05.00.01.01.01.00.00.01.02.01.00.02.00.00.02.01.021.01.00.01.04.01.04.00.00.01.02.00.00.00.02.01.01.00.00.00.01.00.01.02.01.00.04.01.00.02.01.00.00.03.00.00.01.01.00.00.03.02.02.00.02.01.01.00.03.01.02.01.01.01.03.04.00.01.00.05.03.02.00.00.01.02.00.03.01.01.02.00.00.01.04.01.01.02.01.07.05.01.01.00.00.03.00.00.00.00.00.01.00.01.01.01.00.01.01.00.00.01.01.02.00.03.01.02.02.05.03.04.00.01.00.00.03.00.02.02.04.06.01.05.04.00.01.00.02.05.01.01.01.01.00.01.01.00.00.00.02.00.00.00.00.00.00.01.00.02.00.01.00.01.00.00.00.00.00.0
101102Achats et ventes sans factures0.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.01.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.02.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.03.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.01.01.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.01.01.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.02.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.02.00.00.00.00.01.00.01.00.00.00.00.00.00.00.00.017.014.06.00.00.00.01.00.00.00.00.00.00.0
102103Infractions à l'exercice d'une profession règlementée0.00.01.01.00.00.00.01.00.02.00.01.01.00.01.01.02.01.01.04.00.00.01.01.01.05.00.00.01.00.00.00.00.01.02.00.00.00.00.02.00.00.00.03.02.00.01.01.00.04.01.02.00.00.00.00.01.00.01.00.01.00.01.00.00.00.00.01.00.00.00.00.00.00.00.01.01.02.01.04.03.00.01.00.01.00.00.01.00.01.00.01.01.02.00.00.01.00.03.02.01.01.00.01.03.01.00.01.00.01.00.00.00.02.00.00.00.00.03.00.01.00.01.03.01.00.01.01.00.00.00.01.01.04.01.04.02.00.01.01.00.01.00.00.00.01.00.01.00.01.00.01.00.00.01.01.00.00.01.01.00.02.03.00.02.07.04.00.04.02.01.00.00.00.00.01.02.00.00.01.01.00.00.00.01.00.00.00.00.00.00.01.01.00.03.00.00.00.00.02.00.00.00.00.01.01.07.00.00.00.02.00.02.00.00.00.00.00.01.01.01.01.00.00.02.00.00.00.00.00.02.01.00.01.00.00.04.02.01.02.01.02.00.00.00.01.02.00.00.00.01.00.01.00.01.00.02.00.00.00.02.00.00.00.00.00.00.00.00.00.04.03.01.00.01.00.00.01.01.01.00.02.00.01.00.01.02.00.03.01.01.02.01.00.01.00.01.00.00.01.00.01.00.01.03.01.00.01.00.04.04.01.01.00.01.00.00.00.03.00.01.00.00.06.00.02.00.01.00.03.01.01.00.02.01.00.03.00.00.00.01.03.01.00.01.01.01.00.01.01.00.00.00.01.00.00.02.02.00.00.00.01.01.01.07.03.03.00.00.00.01.0
103104Infractions au droit de l'urbanisme et de la construction5.015.09.012.05.07.06.03.05.01.01.04.02.02.09.06.013.011.053.073.016.059.09.021.05.05.00.00.03.02.00.04.02.01.03.00.06.026.010.032.04.05.01.019.017.017.04.025.05.04.05.04.02.03.01.01.04.01.02.01.03.015.030.06.05.03.00.01.06.00.02.05.00.05.02.04.012.06.01.02.01.01.05.04.011.03.03.012.04.014.05.02.07.010.09.04.04.04.05.00.08.03.02.01.015.01.045.023.012.023.013.011.016.09.010.013.028.040.013.09.07.013.011.01.01.044.07.011.07.019.013.014.024.053.017.028.058.04.02.08.05.05.02.03.02.05.016.05.04.05.017.03.09.028.07.015.02.04.02.018.02.07.01.09.02.09.03.09.00.04.03.06.05.012.08.09.015.02.01.017.06.01.06.01.03.00.01.02.04.013.02.07.06.06.014.09.07.02.00.06.02.00.04.03.04.03.01.06.02.05.05.02.024.02.02.06.01.04.028.04.06.07.00.01.03.07.03.06.08.03.07.03.07.06.08.013.012.03.04.00.08.04.06.08.017.010.05.01.06.010.03.00.06.01.00.04.06.02.05.026.035.07.027.04.03.06.05.05.01.04.010.011.010.05.07.07.06.08.02.04.01.02.00.01.04.02.06.01.029.014.07.034.020.010.019.020.03.04.01.02.02.03.021.011.016.07.04.021.013.04.02.01.01.07.04.03.01.00.03.011.03.011.028.057.064.053.022.08.011.03.047.011.015.018.00.01.06.01.02.03.02.05.04.09.02.04.011.05.015.04.01.00.021.011.027.019.024.026.02.059.013.032.036.051.011.09.010.00.01.02.01.0
104105Fraudes fiscales1.00.00.01.01.00.00.00.01.00.00.00.00.00.00.00.00.00.08.00.00.00.00.00.01.00.00.00.00.00.00.01.00.01.01.00.00.01.00.00.00.00.00.01.01.00.00.00.00.03.00.01.00.00.00.01.00.00.00.00.00.01.00.01.00.01.01.01.00.00.00.00.00.00.00.00.00.00.00.00.00.00.01.01.01.01.00.00.02.00.01.00.00.00.00.01.01.00.00.00.00.00.00.01.01.00.01.01.02.00.00.01.01.02.00.00.01.02.03.00.02.03.00.00.01.01.00.00.00.02.00.00.01.01.00.01.01.01.00.00.00.00.00.00.00.00.01.01.01.02.00.00.01.01.00.01.00.01.00.00.00.00.00.01.00.02.01.00.02.00.00.00.00.00.00.01.02.01.00.00.00.00.00.02.00.02.00.00.00.00.00.00.00.00.00.00.00.00.00.02.00.01.00.00.01.00.00.03.00.00.01.00.01.00.01.00.03.00.01.00.03.04.01.00.01.00.00.01.00.01.00.00.01.00.00.02.00.01.00.00.00.00.00.01.01.03.01.00.00.00.00.01.00.01.00.01.01.00.00.00.01.00.00.02.00.00.01.00.00.00.01.01.00.00.00.01.02.03.01.00.01.01.00.00.00.02.00.00.01.01.00.02.00.00.00.00.00.00.00.00.01.00.03.00.02.00.00.00.00.00.00.00.00.00.02.00.01.01.00.00.02.00.05.05.06.00.02.01.00.00.02.01.00.04.00.00.00.00.00.00.00.00.00.02.00.04.01.04.00.00.01.01.02.02.01.00.00.00.00.08.00.01.00.04.01.00.00.00.00.00.00.0
105106Autres délits économiques et financiers0.01.02.05.01.01.02.02.00.01.00.00.00.01.00.01.00.03.08.00.00.01.02.00.01.04.00.01.00.03.00.04.03.00.01.02.01.02.01.01.02.01.00.02.02.01.00.04.00.02.02.01.01.00.03.02.00.00.00.04.00.02.01.00.01.01.01.01.01.00.02.01.01.00.02.00.01.02.01.00.00.00.00.00.04.02.01.03.03.01.01.00.01.02.03.00.01.00.01.03.02.00.01.00.01.00.07.03.02.05.00.00.02.02.00.00.02.02.03.01.06.012.04.01.02.03.05.04.03.01.01.00.01.01.00.01.02.04.02.04.01.01.02.01.00.00.03.01.01.02.01.00.00.01.01.02.00.00.00.03.00.00.03.02.00.02.010.03.01.01.00.01.00.03.00.04.00.00.00.03.02.00.01.01.00.01.00.00.01.02.00.00.00.00.00.02.01.01.01.00.01.01.00.00.00.02.00.04.00.00.00.01.01.01.01.03.00.03.01.00.01.04.00.00.00.01.01.00.00.01.01.01.02.03.00.01.00.02.05.02.01.01.01.03.01.02.00.00.00.02.00.01.02.02.00.01.00.00.01.04.04.00.01.00.00.00.01.01.00.01.06.02.00.00.00.06.03.02.03.00.01.00.00.00.00.00.02.00.02.05.02.05.05.02.02.01.00.01.00.01.03.00.02.08.04.03.02.01.03.00.00.010.00.04.00.00.01.00.00.01.02.02.01.02.08.06.03.02.00.02.00.01.00.06.01.01.03.00.03.01.01.01.00.01.01.02.01.03.02.04.01.04.03.01.01.01.01.00.012.09.019.04.06.04.01.02.01.01.00.05.00.0
106107Autres délits105.0175.0218.0279.082.0166.0130.0118.0129.052.065.0134.024.023.086.078.065.095.0327.0179.084.0172.048.0105.0101.0125.00.059.088.0130.030.078.0112.042.095.0204.0119.0154.079.0175.061.0110.090.0224.0187.0125.0120.0224.0106.0176.060.0108.064.075.081.040.073.0113.0101.0100.0102.0160.0202.0119.076.092.097.088.0140.053.0109.0138.070.094.0154.0132.0120.0271.068.0112.079.082.0109.0128.0141.0187.0104.0127.040.0114.0155.0147.0155.0120.0143.0138.0161.0127.0137.087.0149.0156.087.0135.0165.0108.078.072.040.0107.059.038.039.0152.0131.063.0198.0172.0329.091.0272.0334.0249.0113.0142.0174.0186.0211.0217.0155.0307.0199.0141.0526.0111.0228.0217.0138.0127.0304.0127.0235.080.094.070.0171.0116.0118.0133.0316.0205.096.0192.0311.0162.0260.0117.080.090.0253.089.098.087.0183.057.0201.0104.086.0105.070.0125.085.0138.0151.0151.0255.0204.0120.0111.0262.0182.073.078.083.0148.0171.088.021.076.0164.0115.0115.0101.0127.0148.079.078.063.0132.0115.097.048.065.084.0157.0155.098.0202.068.077.0153.0110.0201.098.0109.0147.075.0114.0186.083.068.0147.055.087.0104.0155.0174.0177.093.0115.0199.059.0109.0235.0218.0179.0217.0235.0197.0119.0170.0183.091.0124.0109.0140.097.040.0102.0141.0116.069.087.078.0102.0113.027.072.0103.0121.0216.079.0170.0169.0156.0126.0142.0223.056.0112.0169.0230.0202.0187.0221.0254.0125.0213.0169.0182.067.0129.0118.072.0112.0222.0247.0127.0124.0188.089.0330.0260.0132.0155.0147.079.056.0135.0110.0127.0112.0162.081.0237.0120.088.0154.0193.0155.0117.0181.089.0157.0106.0140.0156.062.0203.0184.092.0128.0228.0271.0209.0186.065.0194.062.0101.0169.0202.0316.0302.095.0102.0262.085.098.0109.0125.0150.0130.0155.0121.0280.0172.0318.0214.0212.0228.0137.0185.0190.0132.0115.0113.0171.0117.0270.0271.0151.0188.0218.087.089.0308.041.052.0117.017.0